Percepts and Concepts Laboratory

 

Publications & Abstracts

Key

Collective = Collective behavior and group psychology

Similarity = Similarity and comparison making

Concepts = Category learning, concept learning, and conceptual representation

Complex = Complex systems, both how people learn about them, and as models of human cognition

Learning = Learning sciences and educational applications of cognitive science

Perception = Perception and perceptual learning

  1. Goldstone, R. L., Braithwaite, D.  W., & Byrge, L. A. (in press).  Perceptual learning.  In N. M. Seel (Ed.) Encyclopedia of the Sciences of Learning.  Heidelberg, German: Springer Verlag GmbH. 
    Learning Perception
    Perceptual learning consists of long-lasting changes to an organismʼs perceptual system that improve its ability to respond to its environment in specific ways. These changes persist over time; more ephemeral perceptual changes are typically considered to be adaptation, attentional processes, or strategy shifts, rather than perceptual learning. These changes are due to environmental inputs; perceptual changes not coupled to the environment are considered maturation, rather than learning. Perceptual learning benefits an organism by tailoring the processes that gather information to the organismʼs needs for and uses of information.
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  2. Goldstone, R. L., & Day, S. B. (in press).  Similarity. In H. Pashler (Ed.) The Encyclopedia of Mind. SAGE Reference: Thousand Oaks, CA.
    Similarity Concepts
    An enormous amount of ink has been spilled in the psychology literature on the topic of similarity.  There are two reasons that this seemingly intuitive and prosaic concept has been the subject of such intense scrutiny.  First, there is virtually no area of cognitive processing in which similarity does not seem to play a role.  William James observed that “This sense of Sameness is the very keel and backbone of our thinking” (James 1890/1950: 459).  Ivan Pavlov first noted that dogs would generalize their learned salivation response to new sounds as a function of their similarity to the original tone, and this pattern of generalization appears to be ubiquitous across species and stimuli.  People group things together based on their similarity, both during visual processing and categorization.  Research suggests that memories are retrieved when they involve similar features or similar processing to a current situation.  Problem solutions are likely to be retrieved from similar prior problems, inductive inference is largely based on the similarity between the known and unknown cases, and the list goes on and on. 
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  3. Braithwaite, D. W., & Goldstone, R. L. (2012).  Inducing mathematical concepts from specific examples: The role of schema-level variation.  Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society.  (pp. 138-143).  Sapporo, Japan: Cognitive Science Society.
    Learning Concepts
    Previous research suggests that comparing multiple specific examples of a general concept can promote knowledge transfer. The present study investigated whether this approach could be made more effective by systematic variation in the semantic content of the specific examples. Participants received instruction in a mathematical concept in the context of several examples, which instantiated either a single semantic schema (non-varied condition) or two different schemas (varied condition). Schema-level variation during instruction led to better knowledge transfer, as predicted. However, this advantage was limited to participants with relatively high performance before instruction. Variation also improved participants’ ability to describe the target concept in abstract terms. Surprisingly, however, this ability was not associated with successful knowledge transfer.
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  4. Carvalho, P. F., & Goldstone, R. L. (2012).  Category structure modulates interleaving and blocking advantage in inductive category acquisition.   Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society.  (pp. 186-191).  Sapporo, Japan: Cognitive Science Society.
    Learning Concepts Similarity
    Research in inductive category learning has demonstrated that interleaving exemplars of categories results in better performance than presenting each category in a separate block. Two experiments indicate that the advantage of interleaved over blocked presentation is modulated by the structure of the categories being presented. More specifically, interleaved presentation results in better performance for categories with high within- and between-category similarity while blocked presentation results in better performance for categories with low within- and between-category similarity.
    This interaction is predicted by accounts in which blocking promotes discovery of features shared by the members of a category whereas interleaving promotes discovery of features that discriminate between categories.
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  5. Engle, J. T. Feng, Y., Goldstone, R. L. (2012). Mining relatedness graphs for data integration.  Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society.  (pp. 1524-1529).  Sapporo, Japan: Cognitive Science Society.
    Concepts Similarity
    In this paper, we present the AbsMatcher system for schema matching which uses a graph based approach. The primary contribution of this paper is the development of new types of relationships for generating graph edges and the effectiveness of integrating schemas using those graphs. AbsMatcher creates a graph of related attributes within a schema, mines similarity between attributes in different schemas, and then combines all information using the ABSURDIST graph matching algorithm. The attribute-to-attribute relationships this paper focuses on are semantic in nature and have few requirements for format or structure. These relationships sources provide a baseline which can be improved upon with relationships specific to formats, such as XML or a relational database. Simulations demonstrate how the use of automatically mined graphs of within-schema relationships, when combined with cross-schema pair-wise similarity, can result in matching accuracy not attainable by either source of information on its own.
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  6. Hendrickson, A. T., Carvalho, P. F., & Goldstone, R. L. (2012).  Going to extremes: The influence of unsupervised categories on the mental caricaturization of faces and asymmetries in perceptual discrimination.  Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society.  (pp. 1662-1667).  Sapporo, Japan: Cognitive Science Society.
    Learning Concepts Perception
    Recent re-analysis of traditional Categorical Perception (CP) effects show that the advantage for between category judgments may be due to asymmetries of within-category judgments (Hanley & Roberson, 2011). This has led to the hypothesis that labels cause CP effects via these asymmetries due to category label uncertainty near the category boundary. In Experiment 1 we demonstrate that these “within-category” asymmetries exist before category training begins. Category learning does increase the within-category asymmetry on a category relevant dimension but equally on an irrelevant dimension. Experiment 2 replicates the asymmetry found in Experiment 1 without training and shows that it does not increase with additional exposure in the absence of category training. We conclude that the within-category asymmetry may be a result of unsupervised learning of stimulus clusters that emphasize extreme instances and that category training increases this caricaturization of stimulus representations.
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  7. Hendrickson, A. T., Kachergis, G., Fausey, C. M., & Goldstone, R. L. (2012).  Re-learning labeled categories reveals structured representations.  Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society.  (pp. 1668-1673).  Sapporo, Japan: Cognitive Science Society.
    Learning Concepts Perception
    How do people learn to group and re-group objects into labeled categories? In this paper, we examine mechanisms that guide how people re-represent categories. In two experiments, we examine what is easy and what is hard to relearn as people update their knowledge about labeled groups of objects. In Study 1, we test how people learn and re-learn to group objects that share no perceptual features. Data suggest that people easily learn to re-label objects when the category structure remains the same. In Study 2, we test whether more general types of labeling conventions -- words that do or do not correspond with object similarities -- influence learning and re-learning. Data suggest that people are able to learn either kind of convention and may have trouble switching between them when re-structuring their knowledge. Implications for category learning, second language acquisition and updating representations are discussed.
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  8. Ottmar, E., Landy, D., & Goldstone, R. L. (2012).  Teaching the Perceptual Structure of Algebraic Expressions: Preliminary Findings from the Pushing Symbols Intervention.  Proceedings of the Thirty- Fourth Annual Conference of the Cognitive Science Society.  (pp. 2156-2161).  Sapporo, Japan: Cognitive Science Society.
    Learning Concepts Perception
    We describe an intervention being developed by our research team, Pushing Symbols (PS). This intervention is designed to encourage learners to treat symbol systems as physical objects that move and change over time according to dynamic principles. We provide students with the opportunities to explore algebraic structure by physically manipulating and interacting with concrete and virtual symbolic systems that enforce rules through constraints on physical transformations. Here we present an instantiation of this approach aimed at helping students learn the structure of algebraic notation in general, and in particular learn to simplify like terms. This instantiation combines colored symbol tiles with a new touchscreen software technology adapted from the commercial Algebra Touch software. We present preliminary findings from a study with 70 middle-school students who participated in the PS intervention over a three-hour period.
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  9. Terai, A., & Goldstone, R. L. (2012).  An Experimental Examination of Emergent Features in Metaphor Interpretation Using Semantic Priming Effects. Proceedings of the Thirty- Fourth Annual Conference of the Cognitive Science Society.  (pp. 2399-2404).  Sapporo, Japan: Cognitive Science Society.
    Concepts Similarity
    In comprehension of the metaphor “TOPIC is VEHICLE,” emergent features in the interpretation of metaphors are characteristic neither of the topic nor the vehicle. An experiment examines the hypothesis that new features emerge as metaphoric interpretations through association with nonemergent features connected with the topic, vehicle, or both. In the experiment, participants were presented with a nonemergent feature as a prime, a metaphor, and an emergent feature, sequentially. Participants were then asked to respond as to whether the emergent feature is an appropriate interpretation of the metaphor. The results showed that primed non-emergent features derived from the vehicle facilitate the recognition of emergent features. The results support an account in which new features emerge through two processes – non-emergent features are recognized as interpretations of the metaphor and then these non-emergent features facilitate the recognition of emergent features.
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  10. Day, S. B., & Goldstone, R. L. (2012).  The import of knowledge export: Connecting findings and theories of transfer of learning.  Educational Psychologist, 47 , 153-176.
    Learning Concepts
    After more than 100 years of interest and study, knowledge transfer remains among the most challenging, contentious, and important issues for both psychology and education. In this article, we review and discuss many of the more important ideas and findings from the existing research and attempt to bridge this body of work with the exciting new research directions suggested by the following articles.
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  11. Goldstone, R. L., & Day, S. B. (2012).  Introduction to "New Conceptualizations of Transfer of Learning.”  Educational Psychologist, 47, 149-152.
    Learning Concepts
    Understanding how to get learners to transfer their knowledge to new situations is a topic of both theoretical and practical importance. Theoretically, it touches on core issues in knowledge representation, analogical reasoning, generalization, embodied cognition, and concept formation. Practically, learning without transfer of what has been learned is almost always unproductive
    and inefficient. Although schools often measure the efficiency of learning in terms of speed and retention of knowledge, a relatively neglected and subtler component of efficiency is the generality and applicability of the acquired knowledge. This special issue of Educational Psychologist collects together new approaches toward understanding and fostering appropriate transfer in learners. Three themes that emerge from the collected articles are (a) the importance of the perspective/stance of the learner for achieving robust transfer, (b) the neglected role of motivation in determining transfer, and (c) the existence of specific, validated techniques for teaching with an eye toward facilitating students’ transfer of their learning.
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  12. Son, J. Y., Smith, L. B., Goldstone, R. L., & Leslie, M. (2012).  The Importance of being interpreted: Grounded words and children’s relational reasoning, Frontiers in Developmental Psychology, 3, 1-12.
    Similarity Learning Concepts
    Although young children typically have trouble reasoning relationally, they are aided by the presence of relational words (e.g., Gentner & Rattermann, 1991). They also reason well about commonly experienced event structures (e.g., Fivush, 1984).  Relational words may benefit relational reasoning because they activate well-understood event structures.  Two candidate hypotheses were tested: (1) the Schema hypothesis, according to which words help relational reasoning because they are grounded in schematized experiences  and (2) the Optimal Vagueness hypothesis, by which words benefit relational reasoning because the activated schema is open enough (without too much specificity) so that it can be applied analogically to novel problems. Four experiments examine these two hypotheses by examining how training with a label influences schematic interpretations of a scene, the kinds of scenes that are conducive to schematic interpretations, and whether children must figure out the interpretation themselves to benefit from the act of interpreting a scene as an event.  Experiment 1 shows the superiority of schema-evoking words over words that do not connect to schematized experiences.  Experiments 2 and 3 further reveal that these words must be applied to vaguely related perceptual instances rather than unrelated or concretely related instances in order to draw attention to relational structure.  Experiment 4 provides evidence that even when children do not work out an interpretation for themselves, just the act of interpreting an ambiguous scene is potent for relational generalization.  The present results suggest that relational words (and in particular their meanings) are created from the act of interpreting a perceptual situation in the context of a word grounded in meaningful experiences.
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  13. Braithwaite, D. W., & Goldstone, R. L. (2011). Effects of grounded and formal representations on combinatorics learning. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 3431-3436). Boston, Massachusetts: Cognitive Science Society.
    Learning Concepts
    Two experiments examined the differential effects of ground- ed and formal representations on learning of mathematics. Both involved combinatorics, using outcome listing and com- binatorics formulas as examples of grounded and formal rep- resentations, respectively. Experiment 1 compared perfor- mance on near and far transfer problems following instruc- tions involving listing or formulas. Instruction in formulas led to more near transfer, while far transfer performance did not differ by condition. Experiment 2 compared performance fol- lowing four types of instruction: listing only, formulas only, listing fading (listing followed by formulas), and listing intro- duction (formulas followed by listing). The listing fading condition led to performance on par with the formulas only condition, and for near transfer problems, significantly higher than the listing introduction and pure listing conditions. The results support the inclusion of grounded representations in combinatorics instruction, and suggest that such representa- tions should precede rather than follow formal representations in the instructional sequence.
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  14. Byrge, L. A., & Goldstone, R. L. (2011).  Distinguishing levels of grounding that underlie transfer of learning.  Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society.  (pp. 2818-2823).  Boston, Massachusetts: Cognitive Science Society.
    Perception Learning Concepts
    We find that transfer of learning from a perceptually concrete simulation to an isomorphic but superficially dissimilar text- based problem is sensitive to the congruence between the force dynamics common to both systems and the kinesthetic schema induced via action in the first, perceptually concrete, simulation. Counterintuitively, incompatibility between the force dynamics and the kinesthetic schema has a beneficial effect on transfer, relative to compatibility as well as an unrelated control. We suggest that this incompatibility between action and system dynamics may make the system's relational structure more salient, leading to a more flexible conceptualization that ultimately benefits transfer. In addition, we suggest that too much "action concreteness" in hands-on learning may actually limit transfer, by fostering an understanding that is tied to that action and therefore less available for transfer in situations where that action is no longer relevant.
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  15. Carvalho, P. F., & Goldstone, R. L. (2011). Sequential similarity and comparison effects in category learning. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 2977-2982). Boston, Massachusetts: Cognitive Science Society.
    Similarity Learning Concepts
    Order effects in category learning have been previously demonstrated. Specifically, alternation between exemplars of two categories has been shown to improve category learning and discrimination, compared to presenting exemplars of each category in separate blocks. However, the mechanisms under- lying order effects are still not completely known. Remaining issues pertain to the relevance of within and between category similarities, and the role of comparing sequentially presented objects. We present two experiments: in Experiment 1 within- and between-category similarity are manipulated simultane- ously with presentation schedule. In Experiment 2, alternation between categories is compared to two blocked conditions: one in which very similar stimuli are presented successively, and another in which they are dissimilar. Our results show a clear overall advantage of low similarity in categorization performance, but no effect of presentation schedule. Also, al- ternation between categories is shown to result in better per- formance than the blocked condition with more dissimilar stimuli.
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  16. Day, S., & Goldstone, R. L. (2011).  Analogical transfer from a simulated physical system.  Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 551-567.
    Similarity Learning Concepts Perception
    Previous research has consistently found that spontaneous analogical transfer is strongly tied to concrete and contextual similarities between the cases. However, that work has largely failed to acknowledge that the relevant factor in transfer is the similarity between individuals' mental representations of the situations, rather than the overt similarities between the cases themselves. Across several studies, we find that participants are able to transfer strategies learned from a perceptually concrete simulation of a physical system to a task with very dissimilar content and appearance. This transfer is reflected in better performance on the transfer task when its underlying dynamics are consistent rather than inconsistent with the preceding training task. Our data indicate that transfer in these tasks relies on the perceptual and spatial nature of the training task, but does not depend on direct interaction with the system, with participants performing equally well after simply observing the concrete simulation. We argue that participants in these studies are using the concrete, spatial, dynamic information presented in the training simulation as the basis for a concretely similar mental model of the dissimilar transfer task. Unexpectedly, our data consistently showed that transfer was independent of reported recognition of the analogy between tasks: while such recognition was associated with better overall performance, it was not associated with better transfer (in terms of applying an appropriate strategy). Together, these findings suggest that analogical transfer between overtly dissimilar cases may be much more common—and much more relevant to our cognitive processing—than is generally assumed.
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  17. Day, S. B., Manlove, S., & Goldstone, R. L. (2011).  Transfer, and the effects of context outside of the training task.  Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society.  (pp. 2637-2642).  Boston, Massachusetts: Cognitive Science Society.
    Complex Learning Concepts
    While the use of concrete, contextualized and personally relevant examples can benefit learners in terms of comprehension and motivation, these types of examples can come with a cost. Examples may become too bound to their particular context, and individuals may have a difficult time recognizing when the underlying principles are relevant in new situations. In the current study, we provide evidence that contextualization may impair knowledge transfer even when that context occurs outside of the training example itself. Specifically, when students were taught about positive feedback systems in the context of polar ice-albedo effects, those individuals that had previously learned about the effects of global warming on polar bear populations showed reliably poorer transfer performance.
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  18. Frey, S., & Goldstone, R. L. (2011).  Going with the group in a competitive game of iterated reasoning.  Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society.  (pp. 1912-1917).  Boston, Massachusetts: Cognitive Science Society.
    Collective Complex
    In some strategic games, thinking ahead about other players' reasoning can lead to better predictions about what they will do. In other games, infinitely iterated reasoning ultimately prescribes random play. In an online experiment of strategic thinking in groups, we tested participants in a game with the formal structure of a random game, but the superficial struc- ture of a game that rewards iterated reasoning. We found that participants conformed to the superficial structure of the game, and earned more than they would have by playing randomly. We estimated how many steps participants thought ahead in the game and discovered implicit coordination at the group level. Participants unexpectedly "matched" their degree of iterated thinking to each other.
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  19. Goldstone, R. L., Landy, D., & Brunel, L. (2011). Improving Perception to Make Distant Connections Closer. Frontiers in Perception Science.Frontiers in Perception Science, 2:385, 1-10.
    Learning Perception
    One of the challenges for perceptually grounded accounts of high-level cognition is to explain how people make connections and draw inferences between situations that superficially have little in common.  Evidence suggests that people draw these connections even without having explicit, verbalizable knowledge of their bases.  Instead, the connections are based on sub-symbolic representations that are grounded in perception, action, and space.  One reason why people are able to spontaneously see relations between situations that initially appear to be unrelated is that their eventual perceptions are not restricted to initial appearances.  Training and strategic deployment allow our perceptual processes to deliver outputs that would have otherwise required abstract or formal reasoning.  Even without people having any privileged access to the internal operations of perceptual modules, these modules can be systematically altered so as to better subserve our high-level reasoning needs.  Moreover, perceptually-based processes can be altered in a number of ways to closely approximate formally sanctioned computations.
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  20. Goldstone, R. L., Son, J. Y, & Byrge, L. (2011).  Early perceptual learning.  Infancy, 16, 45-51.
    Learning Perception
    Bhatt and Quinn (2011) present a compelling case that human learning is early in two very different, but interacting, senses. Learning is developmentally early in that even infants show strikingly robust adaptation to the structures present in their world. Learning is also early in an information processing sense because infants' adapt their perceptual encodings and organizations at an early stage of neural processing. Both senses of ''early'' speak to the importance of learning because they imply that learners are adapting their representations of their environment in a way that affects all ''down-stream'' processing. Developmentally speaking, the learning that an infant enacts serves as the groundwork for all subsequent learning. In terms of information processing, adapting early-stage sensory and perceptual processes in turn affects all subsequent cognitive processes. There is evidence from neuroscience that interactions with an environment do cause early changes to primarysensory cortices (Goldstone, 1998; Vogels, 2010). One might generally suppose that it is advisable to be conservative in making such environment driven cortical changes, given the ripples of influence caused by early learning in both senses. Manipulating grounding representations is a risky proposition. However, the evidence indicates that systems that need to respond effectively to their environment need to engage in both kinds of learning.
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  21. Roberts, M. E., & Goldstone, R. L. (2011).  Adaptive Group Coordination and Role Differentiation.  PLoS One, 6, 1-8.
    Collective Complex
    Many real world situations (potluck dinners, academic departments, sports teams, corporate divisions, committees, seminar classes, etc.) involve actors adjusting their contributions in order to achieve a mutually satisfactory group goal, a win-win result. However, the majority of human group research has involved situations where groups perform poorly because task constraints promote either individual maximization behavior or diffusion of responsibility, and even successful tasks generally involve the propagation of one correct solution through a group. Here we introduce a group task that requires complementary actions among participants in order to reach a shared goal. Without communication, group members submit numbers in an attempt to collectively sum to a randomly selected target number. After receiving group feedback, members adjust their submitted numbers until the target number is reached. For all groups, performance improves with task experience, and group reactivity decreases over rounds. Our empirical results provide evidence for adaptive coordination in human groups, and as the coordination costs increase with group size, large groups adapt through spontaneous role differentiation and self-consistency among members. We suggest several agent-based models with different rules for agent reactions, and we show that the empirical results are best fit by a flexible, adaptive agent strategy in which agents decrease their reactions when the group feedback changes. The task offers a simple experimental platform for studying the general problem of group coordination while maximizing group returns, and we distinguish the task from several games in behavioral game theory.
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  22. Sang, K., Todd, P. M., & Goldstone, R. L. (2011). Learning near-optimal search in a minimal explore/exploit task. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 2800-2805). Boston, Massachusetts: Cognitive Science Society.
    Learning
    How well do people search an environment for non-depleting resources of different quality, where it is necessary to switch between exploring for new resources and exploiting those already found? Employing a simple card selection task to study exploitation and exploration, we find that the total resources accrued, the number of switches between exploring and exploiting, and the number of trials until stable exploitation becomes more similar to those of the optimal strategy as experience increases across searches. Subjects learned to adjust their effective (implicit) thresholds for exploitation toward the optimal threshold over 30 searches. Those implicit thresholds decrease over turns within each search, just as the optimal threshold does, but subjects' explicitly stated exploitation threshold increases over turns. Nonetheless, both the explicit and learned implicit thresholds produced performance close to optimal.
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  23. Son, J. Y., Smith, L. B., & Goldstone, R. L. (2011). Connecting instances to promote children's relational reasoning.  Journal of Experimental Child Psychology, 108, 260-277. 
    Learning Concepts Perception Similarity
    The practice of learning from multiple instances seems to allow children to learn about relational structure. The experiments reported here have focused on two issues regarding relational learning from multiple instances: (1) what kind of perceptual situations foster such learning and (2) how particular object properties, such as complexity or similarity, interact with relational learning. Two kinds of perceptual situations were of interest here: simultaneous view, where instances are viewed at once, and sequential view, instances are viewed one at a time, one right after the other. We examine the influence of particular perceptual situations and object properties using two tests of relational reasoning: a common match-to-sample task (where new instances are compared to a common sample) and a variable match-to-sample task (where new instances are compared to a sample that varies on each trial). Experiments 1 and 2 indicate that simultaneous presentation of even highly dissimilar instances, one simple and one complex, effectively connects them together and improves relational generalization in both match-to-sample tasks. Experiment 3 showed simple samples are more effective than complex ones in the common match-to-sample task. However, when one instance is not used a common sample and various pairs of instances are simply compared (Experiment 4), simple and rich instances are equally effective at promoting relational learning. These results bear on our understanding of how children connect instances and how those initial connections affect learning and generalization.
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  24. Terai, A. & Goldstone, R. L. (2011).  Processing emergent features in metaphor comprehension.  Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society.  (pp. 2043-2048).  Boston, Massachusetts: Cognitive Science Society.
    Similarity Concepts
    This study examines the processing of emergent features in metaphors. Emergent features are metaphoric interpretations that are characteristic neither of the target nor the vehicle. In the first experiment, participants were asked to respond as to whether a verbal feature is an appropriate interpretation of the metaphor, which was presented as a prime. They are asked to respond immediately after a tone is presented which has a variable temporal lag after the feature. The timing of each tone controlled the participants' response times. The results show that the response deadline given to the participants only slightly affected their judgments. In a second experiment, the time to interpret a metaphor was controlled by varying the pre- sentation time of the metaphor. The results showed that emer- gent features require more time for recognition as a metaphoric interpretation than do non-emergent features. The results sup- port the hypothesis that interaction among features causes feature emergence.
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  25. Wisdom, T. N., & Goldstone, R. L. (2011).  Innovation, imitation, and problem-solving in a networked group.  Nonlinear Dynamics, Psychology, and Life Sciences, 15, 229-252.
    Collective Complex
    We implemented a problem-solving task in which groups of participants simultaneously played a simple innovation game in a complex problem space, with score feedback provided after each of a number of rounds. Each participant in a group was allowed to view and imitate the guesses of others during the game. The results showed the use of social learning strategies previously studied in other species, and demonstrated benefits of social learning and nonlinear effects of group size on strategy and performance. Rather than simply encouraging conformity, groups provided information to each individual about the distribution of useful innovations in the problem space. Imitation facilitated innovation rather than displacing it, because the former allowed good solutions to be propagated and preserved for further cumulative innovations in the group. Participants generally improved their solutions through the use of fairly conservative strategies, such as changing only a small portion of one’s solution at a time, and tending to imitate solutions similar to one’s own. Changes in these strategies over time had the effect of making solutions increasingly entrenched, both at individual and group levels. These results showed evidence of nonlinear dynamics in the decentralization of innovation, the emergence of group phenomena from complex interactions of individual efforts, stigmergy in the use of social information, and dynamic tradeoffs between exploration and exploitation of solutions. These results also support the idea that innovation and creativity can be recognized at the group level even when group members are generally cautious and imitative.
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  26. Bechtel, W., Behrmann, M., Chater, N., Glushko, R. J., Goldstone, R. L., & Smolensky, P. (2010).  The Rumelhart Prize at 10. Cognitive Science, 34, 713-715.
    At the August 2000 meeting of the Cognitive Science Society, Dr. James L. McClelland and Dr. Robert J. Glushko presented the initial plan to honor the intellectual contributions of David E. Rumelhart to cognitive science by awarding an annual prize of $100,000 funded by the Robert J. Glushko and Pamela Samuelson Foundation. McClelland was a close collaborator of Rumelhart, and together they had written numerous articles and books on parallel distributed processing. Glushko, who had been Rumelhart's PhD student in the late 1970s and a Silicon Valley entrepreneur in the 1990s, is currently an adjunct professor at the University of Califonria, Berkeley. Rumelhart had just retired from Stanford University in 1998, suffering from Pick's disease, a degenerative neurological illness. The David E. Rumelhart prize was conceived to honor outstanding research in formal approaches to human cognition. Rumelhart's own seminal contributions to cognitive science included both connectionist and symbolic models, employing both computational and mathematical tools. These contributions progressed from his early work on analogies and story grammars to the development of back-propagation and the use of parallel, distributed processing to model various cognitive abilities. Critically, Rumelhart believed that future progress in cognitive science would depend upon researchers being able to develop rigorous, formal theories of mental structures and processes.
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  27. Day, S., & Goldstone, R. L. (2010). The Effects of Similarity and Individual differences on Comparison and Transfer. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.  (pp. 465-470).  Portland, Oregon: Cognitive Science Society.
    Similarity Learning Concepts
    Prior research has found that while people are generally quite poor at recognizing when a new situation is structurally similar to a known case, comparison of two analogous cases greatly improves the likelihood of achieving such recognition. Our study examines the effects of varying the similarity between these compared cases, both featurally and structurally. We find that between-case similarity has a significant impact on transfer, and that these effects interact with characteristics of the learner.
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  28. Frey, S., & Goldstone, R. L. (2010). Functional Structure and Coordination Failure in Real-Time Group Behavior. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.  (pp. 2093-2098).  Portland, Oregon: Cognitive Science Society.
    Collective Complex
    We reveal spontaneous group formation and differentiation in an online dynamic coordination experiment. We observe increased group stratification and attribute it to increases in pairwise cooperative behavior, rather than uncooperative behavior. Our network analyses document the fine scale structure of coordination failure in the face of many established determinants of coordination success. We explore previous work in coordination failure to frame our own findings. Factors that have been previously shown to improve coordination in discretetime, forced-decision experimental games do not prevent decisive coordination failure in our real-time, asynchronous group decision-making environment.
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  29. Goldstone, R. L., Hills, T. T., & Day, S. B. (2010).  Concept formation.  In. I. B. Weiner & W. E. Craighead (Eds.) The Corsini Encyclopedia of Psychology.  New York: John Wiley & Sons.  (pp. 381-383).
    Similarity Learning Concepts
    A concept is a mentally possessed idea or notion that can be used to categorize information or objects. Over the course of each person's lifetime, thousands of concepts are learned, for nouns like corkscrew, justice, and doorknob, adjectives like green, symmetric, and beautiful, and verbs like kick, climb, and eschew. While some philosophers have maintained that we do not genuinely learn new concepts through induction (Fodor, 1988), most psychologists believe that concepts can be learned, and that the representational capacity of the learner increases as they acquire new concepts. Most efforts have been spent developing accounts of how people acquire and represent concepts, including models based on: rules, prototypes, exemplars, boundaries, and theories.
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  30. Goldstone, R. L., & Landy, D. H. (2010).  Domain-creating constraints. Cognitive Science.
    Learning Perception
    The contributions to this special issue on cognitive development collectively propose ways in which learning involves developing constraints that shape subsequent learning. A learning system must be constrained to learn efficiently, but some of these constraints are themselves learnable. To know how something will behave, a learner must know what kind of thing it is. While this has led previous researchers to argue for domain-specific constraints that are tied to different kinds/domains, an exciting possibility is that kinds/domains themselves can be learned. General cognitive constraints, when combined with rich inputs, can establish domains, rather than these domains necessarily pre-existing prior to learning. Knowledge is structured and richly differentiated, but its “skeleton” must not always be pre-established. Instead, the skeleton may be adapted to fit patterns of co-occurrence, task requirements, and goals. Finally, we argue that for models of development to demonstrate genuine cognitive novelty, it will be helpful for them to move beyond highly pre-processed and symbolic encodings that limit flexibility. We consider two physical models that learn to make tone discriminations. They are mechanistic models that preserve rich spatial, perceptual, dynamic, and concrete information, allowing them to form surprising new classes of hypotheses and encodings.
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  31. Goldstone, R. L. (2010).  Foreward. in I. Gauthier, M. J. Tarr, & D. Bubb (Eds.) Perceptual expertise: Bridging brain and behavior. Oxford, England: Oxford University Press. (pp. v - x).
    Learning Perception
    perceptual learning is important for two reasons—because it is perceptual and because it is learning. Changes to perception are particularly important because they affect all subsequent cognitive processes that occur downstream. There is good evidence, both neurophysiological and behavioral, that perceptual learning can involve early changes to the primary visual, auditory, and somatosensory cortices. One might feel that the early perceptual system ought to be hardwired—it is better not to mess with it if it is going to be depended upon by all processes later in the information processing stream. There is something right with this intuition, but it implicitly buys into a ‘‘stable foundations make strong foundations’’ assumption that it is appropriate for houses of cards, but probably not for flexible cognitive systems. For better models of cognition, we might turn to Birkenstock shoes and suspension bridges, which provide good foundations for their respective feet and cars by flexibly deforming to their charges. Just as a suspension bridge provides better support for cars by conforming to the weight loads, perception supports problem solving and reasoning by conforming to these tasks.

    If perceptual learning is crucially perceptual, it is also crucially learning. Consistent with the ripples of downstream influence that early perceptual changes exert, perceptual systems should generally be designed to change slowly and conservatively, so as not to disrupt their downstream consumers. For this reason, this book’s focus on perceptual expertise is appropriate. Expertise typically requires at least 10 years to attain (Ericsson, Krampe, & Tesch-Römer, 1993), sufficient time to influence perception, not simply decision trees or explicitly memorized strategies. The protracted time course of acquiring new perceptual tools is certainly frustrating for those in the business of judging wines, rock samples, cell structures, dives, or manufacturing flaws. One of the reasons why wisdom can’t be simply told (Bransford, Franks, Vye, & Sherwood, 1989) but rather must be lived is that wisdom is frequently perceptual and thus must be built into one’s neurological wiring.
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  32. Goldstone, R. L., Day, S., & Son, J. Y. (2010). Comparison.  In B. Glatzeder, V. Goel, & A. von Müller (Eds.)  On thinking: Volume II, towards a theory of thinking.  Heidelberg, Germany: Springer Verlag GmbH.  (pp. 103-122).
    Similarity
    It might not be immediately clear why the topic of comparison warrants a whole chapter in a book on human thinking. Of course, we are often required to make decisions that involve comparing two or more alternatives and assessing their relative value. Which car should I buy? Which job is more suited to my long-term goals? Would I rather have the soup or the salad? But in the grand scheme of human cognition, it might seem that such processes could be relegated to a subheading in a chapter on decision making. In fact, comparison is one of the most integral components of human thought. Along with the related construct of similarity, comparison plays a crucial role in almost everything that we do. Furthermore, comparison itself is a powerful cognitive tool—in addition to its supporting role in other mental processes, research has demonstrated that the simple act of comparing two things can produce important changes in our knowledge.
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  33. Goldstone, R. L., & Hendrickson, A. T. (2010). Categorical Perception. Interdisciplinary Reviews: Cognitive Science, 1, 65-78.
    Concepts Perception
    Categorical perception (CP) is the phenomenon by which the categories possessed by an observer influences their perception. Experimentally, CP is revealed when an observer’s ability to make perceptual discriminations between things is better when those things belong to different categories rather than the same category, controlling for the physical difference between the things. We consider several core questions related to CP: Is it caused by innate and/or learned categories, how early in the information processing stream do categories influence perception, and what is the relation between ongoing linguistic processing and CP? CP for both speech and visual entities are surveyed, as are computational and mathematical models of CP. CP is an important phenomenon in cognitive science because it represents an essential adaptation of perception to support categorizations that an organism needs to make. Sensory signals that could be linearly related to physical qualities are warped in a non-linear manner, transforming analog inputs into quasi-digital, quasi-symbolic encodings.
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  34. Goldstone, R. L., Landy, D. H., & Son, J. Y. (2010).  The education of perception. Topics in Cognitive Science, 2, 265-284.
    Learning Complex Perception Concepts
    While the field of perceptual learning has mostly been concerned with low- to middle-level changes to perceptual systems due to experience, we consider high-level perceptual changes that accompany learning in science and mathematics. In science, we explore the transfer of a scientific principle (competitive specialization) across superficially dissimilar pedagogical simulations. We argue that transfer occurs when students develop perceptual interpretations of an initial simulation and simply continue to use the same interpretational bias when interacting with a second simulation. In arithmetic and algebraic reasoning, we find that proficiency in mathematics involves executing spatially explicit transformations to notational elements. People learn to attend mathematical operations in the order in which they should be executed, and the extent to which students employ their perceptual attention in this manner is positively correlated with their mathematical experience. For both science and mathematics, relatively sophisticated performance is achieved not by ignoring perceptual features in favor of deep conceptual features, but rather by adapting perceptual processing so as to conform with and support formally sanctioned responses. These “Rigged Up Perceptual Systems” (RUPS) offer a promising approach to educational reform.
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  35. Goldstone, R. L., Son, J. Y, & Byrge, L. (2010).  Early perceptual learning.  Infancy.
    Learning Perception
    Bhatt and Quinn (2011) present a compelling case that human learning is early in two very different, but interacting, senses. Learning is developmentally early in that even infants show strikingly robust adaptation to the structures present in their world. Learning is also early in an information processing sense because infants' adapt their perceptual encodings and organizations at an early stage of neural processing. Both senses of ''early'' speak to the importance of learning because they imply that learners are adapting their representations of their environment in a way that affects all ''down-stream'' processing. Developmentally speaking, the learning that an infant enacts serves as the groundwork for all subsequent learning. In terms of information processing, adapting early-stage sensory and perceptual processes in turn affects all subsequent cognitive processes. There is evidence from neuroscience that interactions with an environment do cause early changes to primary sensory cortices (Goldstone, 1998; Vogels, 2010). One might generally suppose that it is advisable to be conservative in making such environment-driven cortical changes, given the ripples of influence caused by early learning in both senses. Manipulating grounding representations is a risky proposition. However, the evidence indicates that systems that need to respond effectively to their environment need to engage in both kinds of learning.
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  36. Gureckis, T. M. and Goldstone, R. L. (2010) Schema. In P. C. Hogan (Ed.) The Cambridge Encyclopedia of the Language Sciences.   Cambridge, England: Cambridge University Press.  (pp. 725-727).
    Concepts
    A schema is a high-level conceptual structure or framework that organizes prior experience and helps us to interpret new situations. The key function of a schema is to provide a summary of our past experiences by abstracting out their important and stable components. For example, we might have a schema for a classroom that includes the fact that it typically contains a chalkboard, bookshelves, and chairs. Schemas provide a framework for rapidly processing information in our environment. For example, each time we enter a classroom, we do not have to consider each element in the room individually (e.g., chair, table, chalkboard). Instead, our schemas "fi ll in" what we naturally expect to be present, helping to reduce cognitive load. Similarly, schemas also allow us to predict or infer unknown information in completely new situations. If we read about a third grade classroom in a book, we can use our established classroom schema to predict aspects of its appearance, including the presence of a coatroom and the types of posters that might decorate the walls.
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  37. Hendrickson, A. T., Kachergis, G., Gureckis, T. M., & Goldstone, R. L. (2010). The effect of verbal interference and the internal structure of categories on perceptual discrimination. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.  (pp. 1216-1221).  Portland, Oregon: Cognitive Science Society.
    Learning Perception Concepts
    Recent research has argued that categorization is strongly tied to language processing. For example, language (in the form of verbal category labels) has been shown to influence perceptual discriminations of color (Winawer et al., 2007). However, does this imply that categorical perception is essentially verbally mediated perception? The present study extends recent findings in our lab showing that categorical perception can occur even in the absence of overt labels. In particular, we evaluate the degree to which certain interference tasks (verbal, spatial) reduce the effect of learned categorical perception for complex visual stimuli (faces). Contrary to previous findings, our results show that a verbal interference task does not disrupt learned categorical perception effects for faces. Our results are interpreted in light of the ongoing debate about the role of language in categorization. In particular, we suggest that at least a sub-set of categorical perception effects may be effectively "language-free".
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  38. Hills, T. T., Todd, P. M., & Goldstone, R. L. (2010). Priming a Central Executive Search Process: Exploration and Exploitation in Generalized Cognitive Search Processes.  Journal of Experimental Psychology: General, 139, 560-609.
    Complex Learning
    The trade-off between exploration and exploitation is common to a wide variety of problems involving search in space and mind. The prevalence of this trade-off and its neurological underpinnings led us to propose domain-general cognitive search processes (Hills, Todd, & Goldstone, 2008). We propose further that these are consistent with the idea of a central executive search process that combines goal-handling across subgoal hierarchies. In the present study, we investigate 3 aspects of this proposal. First, the existence of a unitary central executive search process should allow priming from 1 search task to another and at multiple hierarchical levels. We confirm this by showing cross-domain priming from a spatial search task to 2 different cognitive levels within a lexical search task. Second, given the neural basis of the proposed generalized cognitive search process and the evidence that the central executive is primarily engaged during complex tasks, we hypothesize that priming should require search in the sense of a self-regulated making and testing of sequential predictions about the world. This was confirmed by showing that when participants were allowed to collect spatial resources without searching for them, no priming occurred. Finally, we provide a mechanism for the underlying search process and investigate 3 alternative hypotheses for subgoal hierarchies using the central executive as a search process model (CESP). CESP envisions the central executive as having both emergent and unitary processes, with one of its roles being a generalized cognitive search process that navigates goal hierarchies by mediating persistence on and switching between subgoals.
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  39. Landy, D. H., & Goldstone, R. L. (2010).  Proximity and precedence in arithmetic. The Quarterly Journal of Experimental Psychology, 63, 1953-1968.
    Learning Perception
    How does the physical structure of an arithmetic expression affect the computational processes engaged in by reasoners? In handwritten arithmetic expressions containing both multiplications and additions, terms that are multiplied are often placed physically closer together than terms that are added. Three experiments evaluate the role such physical factors play in how reasoners construct solutions to simple compound arithmetic expressions (such as “2 + 3 × 4”). Two kinds of influence are found: First, reasoners incorporate the physical size of the expression into numerical responses, tending to give larger responses to more widely spaced problems. Second, reasoners use spatial information as a cue to hierarchical expression structure: More narrowly spaced subproblems within an expression tend to be solved first and tend to be multiplied. Although spatial relationships besides order are entirely formally irrelevant to expression semantics, reasoners systematically use these relationships to support their success with various formal properties.
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  40. Son, J. Y., Doumas, L. A., & Goldstone, R. L. (2010).  When do words promote analogical transfer?  The Journal of Problem Solving, 3, 52-92.
    Similarity Learning Concepts
    The purpose of this paper is to explore how and when verbal labels facilitate relational reasoning and transfer. We review the research and theory behind two ways words might direct attention to relational information: (1) words generically invite people to compare and thus highlight relations (the Generic Tokens [GT] hypothesis), and/or (2) words carry semantic cues to common structure (the Cues to Specific Meaning [CSM] hypothesis). Four experiments examined whether learning Signal Detection Theory (SDT) with relational words fostered better transfer than learning without relational words in easily alignable and less alignable situations (testing the GT hypothesis) as well as when the relational words matched and mismatched the semantics of the learning situation (testing the CSM hypothesis). The results of the experiments found support for the GT hypothesis because the presence of relational labels produced better transfer when two situations were alignable. Although the CSM hypothesis does not explain how words facilitate transfer, we found that mismatches between words and their labeled referents can produce a situation where words hinder relational learning.
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  41. Theiner, G, Allen, C., & Goldstone, R. L. (2010). Recognizing group cognition. Cognitive Systems Research, 11, 378-395.
    Collective Complex
    In this paper, we approach the idea of group cognition from the perspective of the ''extended mind'' thesis, as a special case of the more general claim that systems larger than the individual human, but containing that human, are capable of cognition (Clark, 2008; Clark & Chalmers, 1998). Instead of deliberating about ''the mark of the cognitive'' (Adams & Aizawa, 2008), our discussion of group cognition is tied to particular cognitive capacities. We review recent studies of group problem solving and group memory which reveal that specific cognitive capacities that are commonly ascribed to individuals are also aptly ascribed at the level of groups. These case studies show how dense interactions among people within a group lead to both similarity-inducing and differentiating dynamics that affect the group's ability to solve problems. This supports our claim that groups have organization-dependent cognitive capacities that go beyond the simple aggregation of the cognitive capacities of individuals. Group cognition is thus an emergent phenomenon in the sense of Wimsatt (1986). We further argue that anybody who rejects our strategy for showing that cognitive properties can be instantiated at multiple levels in the organizational hierarchy on a priori grounds is a ''demergentist,'' and thus incurs the burden of proof for explaining why cognitive properties are ''stuck'' at a certain level of organizational structure. Finally, we show that our analysis of group cognition escapes the ''coupling-constitution'' charge that has been leveled against the extended mind thesis (Adams & Aizawa, 2008).
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  42. Wisdom, T. N., & Goldstone, R. L. (2010). Social Learning and Cumulative Mutual Improvement in a Networked Group.  Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.  (pp. 1405-1410).  Portland, Oregon: Cognitive Science Society.
    Collective
    We used a simple problem-solving game task to study imitation and innovation in groups of participants. Guesses were composed of multiple elements with linear and interactive effects on score, and score feedback was provided after each of a number of rounds. Participants were allowed to view and imitate the guesses of others during each round, and the score information accompanying others' guesses was either shown or hidden in two conditions. When scores were not visible, social learning was impeded; participants were less efficient in their searching of the problem space and achieved lower performance overall. When scores were visible, higher performance was observed, and results indicated a more equitable sharing of productive exploration among participants within groups as a result of selective imitation and cross-participant cumulative mutual innovations.
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  43. Barab, S., Scott, B., Siyahhan, S. Goldstone, R. L., Ingram-Goble, A., Zuiker, S., & Warren, S. (2009).  Transformational play as a curricular scaffold: Using videogames to support science education Journal of Science Education and Technology, 18, 305-320.
    Learning
    Drawing on game-design principles and an underlying situated theoretical perspective, we developed and researched a 3D game-based curriculum designed to teach water quality concepts. We compared undergraduate student dyads assigned randomly to four different instructional design conditions where the content had increasingly level of contextualization: (a) expository textbook condition, (b) simplistic framing condition, (c) immersive world condition, and a (d) single-user immersive world condition. Results indicated that the 3D-dyad and 3D-single user conditions performed significantly better than the electronic textbook group on standardized items. The immersive-world dyad condition also performed significantly better than either the expository textbook or the descriptive framing condition on a performance-based transfer task, and performed significantly better than the expository textbook condition on standardized test items. Implications for science education, and consistent with the goals of this special issue, are that immersive game-based learning environments provide a powerful new form of curriculum for teaching and learning science.
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  44. Gureckis, T. M., & Goldstone, R. L. (2009). How you named your child: Understanding the relationship between individual decision-making and collective outcomes. Topics in Cognitive Science, 1, 651-674.
    Collective Complex
    We examine the interdependence between individual and group behavior surrounding a somewhat arbitrary, real world decision: selecting a name for
    one's child. Using a historical database of the names given to children over the last century in the United States, we nd that naming choices are influenced by both the frequency of a name in the general population, and by its "momentum" in the recent past in the sense that names which are growing in popularity are preferentially chosen. This bias toward rising names is a recent phenomena: in the early part of the 20th century, increasing popularity of a name from one time period to the next was correlated with a decrease in future popularity. However, more recently this trend has reversed. We evaluate a number of formal models that detail how individual decision-making strategies, played out in a large population of interacting agents, can explain these empirical observations. We argue that cognitive capacities for change detection, the encoding of frequency in memory, and biases towards novel or incongruous stimuli may interact with the behavior of other decision makers to determine the distribution and dynamics of cultural tokens such as names.
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  45. Day, S. B., & Goldstone, R. L. (2009).  Analogical transfer from interaction with a simulated physical system. Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, 1406-1411. Amsterdam, Netherlands: Cognitive Science Society.
    Learning
    In two studies, we find that participants are able to transfer strategies learned while interacting with a simulated physical system to a dissimilar and less perceptually-concrete domain. Interestingly, performance on the transfer task was completely unrelated to explicit knowledge of the structural correspondences between the systems. We suggest that direct interaction with a concrete system may lead to a kind of procedural knowledge that provides a good basis for analogical transfer.
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  46. Gerganov, A., Grinberg, M., & Goldstone, R. L. (2009).  Partial position transfer in categorical perception learning Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, 1828-1833. Amsterdam, Netherlands: Cognitive Science Society.
    Perception
    Two experiments are reported. The first shows incomplete transfer of explicit categorical learning at a distance of 4.5 degrees of visual angle and the second is a control experiment with a non-learning task. The results suggest that some early visual plasticity takes place even in a simple, explicit categorical learning task. We claim that perceptual learning is a much more common phenomenon than believed before and that it plays an important role in everyday tasks including higher-level learning.
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  47. Goldstone, R. L. & Gureckis, T. M. (2009).  Collective behavior. Topics in Cognitive Science, 1, 412-438.
    Collective Complex
    The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self-organized collectives, and computational modeling methods for understanding both universal and scenario-specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. Some critical issues surrounding collective behavior are then reviewed, including the questions of ‘‘Does group behavior always reduce to individual behavior?’’ ‘‘Is ‘group cognition’ possible?’’ and ‘‘What is the value of formal modeling for understanding group behavior?’’
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  48. Hendrickson, A T., & Goldstone, R. L. (2009).  Perceptual unitization in part-whole judgments Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, 1084-1089. Amsterdam, Netherlands: Cognitive Science Society.
    Concepts Perception
    Categorization relies upon the vocabulary of features that comprise the target objects. Previous theoretical work (Schyns, Goldstone, & Thibaut, 1998) has argued this vocabulary may change through learning and experience. Goldstone (2000) demonstrated this perceptual learning during a categorization task when new features are added that create a single feature unit from multiple existing units. We present two experiments that expand on that work using whole-part judgments (Palmer, 1978) to elicit the feature representation learned through categorization. The implications for different classes of computational models of categorization are discussed.
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  49. Landy, D. H., & Goldstone, R. L. (2009).  How much of symbolic manipulation is just symbol pushing? Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, 1072-1077. Amsterdam, Netherlands: Cognitive Science Society.
    Learning
    This paper explores the hypothesis that schematic abstraction—rule following—is partially implemented through processes and knowledge used to understand motion. Two experiments explore the mechanisms used by reasoners solving simple linear equations with one variable. Participants solved problems displayed against a background that moved rightward or leftward. Solving was facilitated when the background motion moved in the direction of the numeric transposition required to solve for the unknown variable. Previous theorizing has usually assumed that such formal problems are solved through the repeated application of abstract transformation patterns (rules) to equations, replicating the steps produced in typical worked solutions. However, the current results suggest that in addition to such strategies, advanced reasoners often employ a mental motion strategy when manipulating algebraic forms: elements of the problem are “picked up” and “moved” across the equation line. This demonstration supports the suggestion that genuinely schematic reasoning could be implemented in perceptual-motor systems through the simulated transformation of referential (but physical) symbol systems.
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  50. Roberts, M. E., & Goldstone, R. L. (2009).  Adaptive group coordination, Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society. 2698-2704. Amsterdam, Netherlands: Cognitive Science Society.
    Collective Complex
    Human groups exhibit poor performance in many social situations because task constraints promote either individual maximization behavior or diffusion of responsibility. We introduce a group task that tests human coordination when only a shared group goal exists. Without communication, group members submit numbers in an attempt to collectively sum to a randomly selected number. After receiving group feedback, members adjust their submitted numbers in the next round. Small groups generally outperform large groups, and for all groups, performance improves with task experience, and reactivity to feedback decreases over rounds. Our empirical results and computational modeling provide evidence for adaptive coordination in human groups despite minimal shared history and only indirect communication, and perhaps most interestingly, as the coordination costs increase with group size, large groups adapt through spontaneous role differentiation and self-consistency among members.
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  51. Roberts, M. E., & Goldstone, R. L. (2009).  Sub-optimalities in group foraging and resource competition. , Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society 2371-2377. Amsterdam, Netherlands: Cognitive Science Society.
    Collective Complex
    Previous group foraging research has shown that human groups sub-optimally distribute themselves to resources and display undermatching, with a smaller-than-expected proportion of individuals at the more abundant resource pool. In order to further explore these sub-optimalities, we extended a group foraging paradigm to test three variables: the effects of three resource pools, travel cost between pools, and the size of the pools. Although each condition led to undermatching, the conditions showed significant differences in the extent of undermatching, the frequency of switching between resource pools, the wealth inequality among foragers, and the comparative wealth inequality at different resource pools. The results for the three pool conditions suggest that human groups have difficulty in discriminating the relative value of resource pools. The results for the travel cost conditions indicate that human groups distribute themselves to resources more optimally when individuals can easily switch between pools, which is the opposite of the result found with foraging pigeons. Finally, the results for the pool size conditions indicate that larger pool sizes promote greater undermatching, apparently because individuals inefficiently compete over large areas rather than effectively parceling the pools into smaller, distinct regions.
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  52. Son, J. Y., & Goldstone, R. L. (2009).  Fostering General Transfer with Specific Simulations. Pragmatics and Cognition, 17, 1-42.
    Concepts Complex Learning
    Science education faces the difficult task of helping students understand and appropriately generalize scientific principles across a variety of superficially dissimilar specific phenomena. Can cognitive technologies be adapted to benefit both learning specific domains and generalizable transfer? This issue is examined by teaching students complex adaptive systems with computer-based simulations. With a particular emphasis on fostering understanding that transfers to dissimilar phenomena, the studies reported here examine the influence of different descriptions and perceptual instantiations of the scientific principle of competitive specialization. Experiment 1 examines the role of intuitive descriptions to concrete ones, finding that intuitive descriptions leads to enhanced domain-specific learning but also deters transfer. Experiment 2 successfully alleviated these difficulties by combining intuitive descriptions with idealized graphical elements. Experiment 3 demonstrates that idealized graphics are more effective than concrete graphics even when unintuitive descriptions are applied to them. When graphics are concrete, learning and transfer largely depends on the particular description. However, when graphics are idealized, a wider variety of descriptions results in levels of learning and transfer similar to the best combination involving concrete graphics. Although computer-based simulations can be effective for learning that transfers, designing effective simulations requires an understanding of concreteness and idealization in both the graphical interface and its description.
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  53. Son, J. Y., & Goldstone, R. L. (2009).  Contextualization in perspective. Cognition and Instruction, 27, 51-89.
    Learning
    Instruction abstracted from specific and concrete examples is frequently criticized for ignoring the context-dependent and perspectival nature of learning (e.g., Bruner, 1962, 1966; Greeno, 1997). Yet, in the effort to create personally interesting learning contexts, cognitive consequences have often been ignored. To examine what kinds of personalized contexts foster or hinder learning and transfer, three manipulations of perspective and context were employed to teach participants Signal Detection Theory (SDT). In all cases, application of SDT principles was negatively impacted by manipulations that encouraged participants to consider the perspective of the signal detector (the decision maker in SDT situations): by giving participants active detection experience (Experiment 1), biasing them to adopt a first-person rather than third-person perspective (Experiment 2), or framing the task in terms of a well-known celebrity (Experiment 3). These contexts run the risk of introducing goals and information that are specific to the detector’s point of view, resulting in sub-optimal understanding of SDT.
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  54. Goldstone, R. L., & Wilensky, U. (2008).  Promoting Transfer through Complex Systems Principles. Journal of the Learning Sciences, 17, 465-516.
    Complex Learning
    Understanding scientific phenomena in terms of complex systems principles is both scientifically and pedagogically important. Situations from different disciplines of science are often governed by the same principle, and so promoting knowledge transfer across disciplines makes valuable cross-fertilization and scientific unification possible. Although evidence for this kind of transfer has been historically controversial, experiments and observations of students suggest pedagogical methods to promote transfer of complex systems principles. One powerful strategy is for students to actively interpret the elements and interactions of perceptually grounded scenarios. Such interpretation can be facilitated through the presentation of cases alongside general principles, and by students exploring and constructing computational models of cases. The resulting knowledge can be both concretely grounded yet highly perspective-dependent and generalizeable. We discuss methods for coordinating computational and mental models of complex systems, the roles of idealization and concreteness in fostering understanding and generalization, and other complementary theoretical approaches to transfer.
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  55. Goldstone, R. L., Landy, D., & Son, J. Y. (2008). A well grounded education: The role of perception in science and mathematics. In M. de Vega, A. Glenberg, & A. Graesser (Eds.) Symbols, embodiment, and meaning. Oxford Press (pp . 327-355).
    Learning Perception
    One of the most important applications of grounded cognition theories is to science and mathematics education where the primary goal is to foster knowledge and skills that are widely transportable to new situations. This presents a challenge to those grounded cognition theories that tightly tie knowledge to the specifics of a single situation. In this chapter, we develop a theory learning that is grounded in perception and interaction, yet also supports transferable knowledge. A first series of studies explores the transfer of complex systems principles across two superficially dissimilar scenarios. The results indicate that students most effectively show transfer by applying previously learned perceptual and interpretational processes to new situations. A second series shows that even when students are solving formal algebra problems, they are greatly influenced by non-symbolic, perceptual grouping factors. We interpret both results as showing that high-level cognition that might seem to involve purely symbolic reasoning is actually driven by perceptual processes. The educational implication is that instruction in science and mathematics should involve not only teaching abstract rules and equations but also training students to perceive and interact with their world.
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  56. Goldstone, R. L., Gerganov, A., Landy, D., & Roberts, M. E. (2008). Learning to see and conceive. In L. Tommasi, M. Peterson, & L. Nadel (Eds.) The New cognitive sciences (part of the Vienna Series in Theoretical Biology). Cambridge, MA.: MIT Press. (pp. 163-188).
    Concepts Perception
    Human concept learning depends upon perception. Our concept of Car is built out of perceptual features such as “engine,” “tire,” and “bumper.” However, recent research indicates that the dependency works both ways. We see bumpers and engines in part because we have acquired Car concepts and detected examples of them. Perception both influences and is influenced by the concepts that we learn. We have been exploring the psychological mechanisms by which concepts and perception mutually influence one another, and building computational models to show that the circle of influences is benign rather than vicious.
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  57. Goldstone, R. L., Roberts, M. E., & Gureckis, T. M. (2008).  Emergent Processes in Group Behavior. Current Directions in Psychological Science, 17, 10-15.
    Collective Complex
    Just as networks of neurons create structured thoughts beyond the ken of any individual neuron, so people spontaneously organize themselves into groups to create emergent organizations that no individual may intend, comprehend, or even perceive. Recent technological advances have provided us with unprecedented opportunities for conducting controlled, laboratory experiments on human collective behavior. We describe two experimental paradigms where we attempt to build predictive bridges between the beliefs, goals, and cognitive capacities of individuals and group-level patterns, showing how the members of a group dynamically allocate themselves to resources, and how innovations are spread in a social network. Agent-based computational models have provided useful explanatory and predictive accounts. Together, the models and experiments point to tradeoffs between exploration and exploitation, compromises between individuals using their own innovations and innovations obtained from their peers, and the emergence of group-level organizations such as population waves, bandwagon effects, and spontaneous specialization.
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  58. Goldstone, R. L., Roberts, M. E., Mason, W., & Gureckis, T. (2008). Collective search in concrete and abstract spaces. In T. Kugler, J. C. Smith, T. Connelly, and Y. Sun (Eds.) Decision modeling and behavior in complex and uncertain environments. New York: Springer Press. (pp. 277-308).
    Collective
    Our laboratory has been studying the emergence of collective search behavior from a complex systems perspective. We have developed an internet-based experimental platform that allows groups of people to interact with each other in real time on networked computers. The experiments implement virtual environments where participants can see the moment-to-moment actions of their peers and immediately respond to their environment. Agent-based computational models are used as accounts of the experimental results. We describe two paradigms for collective search – one in physical space and the other in an abstract problem space. The physical search situation concerns competitive foraging for resources by individuals inhabiting an environment consisting largely of other individuals foraging for the same resources. The abstract search concerns the dissemination of innovations in social networks. Across both scenarios, the group-level behavior that emerges reveals influences of exploration and exploitation, bandwagon effects, population waves, and compromises between individuals using their own information and information obtained from their peers.
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  59. Gureckis, T. M., & Goldstone, R. L. (2008).  The effect of internal structure of categories on perception. Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society, (pp. 1876-1881). Washington, D.C.: Cognitive Science Society.
    Concepts Perception
    A novel study is presented that explores the effect that learning internally organized categories has on the ability to subsequently discriminate category members. The results demonstrate the classic categorical perception effect whereby discrimination of stimuli that belong to different categories is improved following training, while the ability to discriminate stimuli belonging to the same category is reduced. We further report a new within-category perceptual effect whereby category members that share the same category label but fall into different sub-clusters within that category are better discriminated than items that share the same category and cluster. The results show that learners are sensitive to multiple sources structure beyond simply the labels provided during supervised training. A computational model is presented to account for the results whereby multiple levels of encoding (i.e., at the item-, cluster-, and category- level) may simultaneously contribute to perception.
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  60. Hills, T. T., Todd, P. M., & Goldstone, R. L. (2008), Search in external and internal spaces. Psychological Science, 19, 676-682.
    Perception
    There is compelling molecular and behavioral evidence that goal-directed cognition is an evolutionary
    descendent of spatial-foraging behavior. Across animal species, similar dopaminergic processes modulate between exploratory and exploitative foraging behaviors and control attention. Consequently, we hypothesized that spatialforaging activity could prime attentional cognitive activity. We examined how searching in physical space influences subsequent search in abstract cognitive space by presenting participants with a spatial-foraging task followed by a repeated Scrabble task involving search for words that could be made from letter sets. Participants who searched through clumpier distributions in space behaved as if words were more densely clumped in the Scrabble task. This was not a function of arousal, but was consistent with predictions of optimal-foraging theory. Furthermore, individual differences in exploratory search were conserved across
    the two types of tasks. Along with the biological evidence, our results support the idea that there are generalized cognitive search processes.
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  61. Janssen, M. A., Goldstone, R. L., Menczer, F., & Ostrom, E. (2008).  Effect of rule choice in dynamic interactive spatial commons. International Journal of the Commons, 2, 288-312.
    Collective
    This paper uses laboratory experiments to examine the effect of an endogenous rule change from open access to private property as a potential solution to over-harvesting in commons dilemmas. A novel, spatial, real-time renewable resource environment was used to investigate whether participants were willing to invest in changing the rules from an open access situation to a private property system. We found that half of the participants invested in creating private property arrangements. Groups who had experienced private property in the second round of the experiment, made different decisions in the third round when open access was re-instituted in contrast to groups who experienced three rounds of open access. At the group level, earnings increased in Round 3, but this was at a cost of more inequality. No significant differences in outcomes occurred between experiments where rules were imposed by the experimental design or chosen by participants.
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  62. Landy, D. H., Jones, M. N., & Goldstone, R. L. (2008).  How the appearance of an operator affects its formal precedence. Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society, , (pp. 2109-2114). Washington, D.C.: Cognitive Science Society
    Learning Perception
    Two experiments test predictions of a visual process-driven model of multi-term arithmetic computation. The visual process model predicts that attention should be drawn toward multiplication signs more readily than toward plus signs, and that narrow spaces should draw gaze comparably to multiplication signs. Although both of these predictions are verified by behavioral response measures and eye-tracking, the visual process model cannot account for patterns of early looking. The results suggest that people strategically deploy visual computation strategies.
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  63. Mason, W. A., Jones, A., & Goldstone, R. L. (2008). Propagation of innovations in networked groups. Journal of Experimental Psychology: General, 137, 422-433.
    Collective Complex
    A novel paradigm was developed to study the behavior of groups of networked people searching a problem space. We examined how different network structures affect the propagation of information in laboratory-created groups. Participants made numerical guesses and received scores that were also made available to their neighbors in the network. The networks were compared on speed of discovery and convergence on the optimal solution. One experiment showed that individuals within a group tend to converge on similar solutions even when there is an equally valid alternative solution. Two additional studies demonstrated that the optimal network structure depends on the problem space being explored, with networks that incorporate spatially-based cliques having an advantage for problems that benefit from broad exploration, and networks with greater long-range connectivity having an advantage for problems requiring less exploration.
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  64. Son, J. Y., Smith, L. B., & Goldstone, R. L. (2008).  implicity and generalization: Short-cutting abstraction in children’s object categorizations. Cognition, 108, 626-638.
    Learning Perception
    Development in any domain is often characterized by increasingly abstract representations. Recent evidence in the domain of shape recognition provides one example; between 18 and 24 months children appear to build increasingly abstract representations of object shape [Smith, L. B. (2003). Learning to recognize objects. Psychological Science, 14, 244– 250]. Abstraction is in part simplification because it requires the removal of irrelevant information. At the same time, part of generalization is ignoring irrelevant differences. The resulting prediction is this: simplification may enable generalization. Four experiments asked whether simple training instances could shortcut the process of abstraction and directly promote appropriate generalization. Toddlers were taught novel object categories with either simple or complex training exemplars. We found that children who learned with simple objects were able to generalize according to shape similarity, typically relevant for early object categories, better than those who learned with complex objects. Abstraction is the product of learning; using simplified – already abstracted instances – can short-cut that learning, leading to robust generalization.
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  65. Wisdom, T. N., Song, X., & Goldstone, R. L. (2008).  The effects of peer information on problem-solving in a networked group. Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society, , (pp. 583-588). Washington, D.C.: Cognitive Science Society
    Collective
    In this experiment, we implemented a problem-solving task in which groups of participants simultaneously play a simple puzzle game, with score feedback provided after each of 24 rounds. Each participant in a group is allowed to view and imitate the guesses of others during the game. Results show that when the utility of others' innovations is unambiguous, individuals base their own solutions on personal innovation and productively imitate other players' innovations early on, and that this tendency to imitate is proportional to the relative amount of information available from others. Average trends of innovation and imitation decreased across rounds as player guesses stabilized and scores increased. Mean scores and imitation increased with group size, while individual innovation decreased. Results are consistent with previously studied social learning strategies in several taxa.
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  66. Ionescu, T., & Goldstone, R. L. (2007). Introduction to a special issue on the Development of Categorization, Cognition, Brain, and Behavior, 11, 629-633.
    Concepts Learning Perception
    Categorization is indubitably an important cognitive process for humans (as well as other animals, Murai, Kosugi, Tomonaga, Tanaka, Matsuzawa, & Itakura, 2005), one that we constantly engage in to adapt to a very rich environment. We have a powerful impulse to interpret our world. This act of interpretation is fundamentally an act of categorization. We can go back in history at least to Aristotle (see his work on Categories, 350 B.C.E.) and along this way we find discussions of categories often appearing in philosophers’ books. The issue of categorization is also an historically early topic in psychology (see Hull’s experiment in 1920), and a considerable amount of research has been continuously dedicated to it up until the present. One could ask then: Why a special issue on categorization at this point in time? Although the general topic of categorization is venerable, relatively recently we cognitive scientists have changed our view about categorization. We have moved from considering taxonomies (or categories based in logic) as the “real,” mature kind of categorization to understanding that there are multiple kinds of similarities that are taken into account when one groups items (Barsalou, 1993, 2003; Medin, Goldstone, & Gentner, 1993; Ross & Murphy, 1999).
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  67. Landy, D., & Goldstone, R. L. (2007).  Formal notations are diagrams: Evidence from a production task. Memory & Cognition, 35, 2033-2040
    Learning Perception
    Although a general sense of the magnitude, quantity, or numerosity of objects is common both in untrained people and in animals, the abilities to deal exactly with large quantities and to reason precisely in complex but well-specified situations—to behave formally, that is—are skills unique to people trained in symbolic notations. These symbolic notations employ typically complex, hierarchically embedded structures, which all extant analyses assume are constructed by concatenative, rule-based processes. The primary goal of this article is to establish, using behavioral measures on naturalistic tasks, that the some of the same cognitive resources involved in representing spatial relations and proximities are also involved in representing symbolic notations: in short, formal notations are a kind of diagram. We examine self-generated productions in the domains of handwritten arithmetic expressions and typewritten statements in a formal logic. In both tasks, we find substantial evidence for spatial representational schemes even in these highly symbolic domains.
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  68. Baldwin D. & Goldstone R.L. (2007). Finding analogies within systems: Constraints on unsegmented matching. Proceedings of the Workshop on Analogies: Integrating Multiple Cognitive Abilities (AnICA07). Nashville, Tennessee.
    Similarity
    The complex structure and organization of knowledge in the human mind is one of the key facets of thought. One of the fundamental cognitive processes that oper- ates over that structure is analogy. A typical compu- tational model of analogy might juxtapose a source do- main and a target domain, such as the solar system and the Bohr-Rutherford (BR) model of an atom (Gentner, 1983). The goal is to find a correspondence mapping between these two domains. Determining a mapping between the source and target domains of a non-trivial size would be intractable without a set of constraints to restrict the set of correspondences that are considered by a human reasoner. Moreover, the mere presence of domains serve as a constraint on mapping. In this paper, we study an alternative problem called unsegmented mapping - correspondence without specification of domains. We show a series of three formal constraints that allow for analogical-like mappings without explicit segmentation. The result, correspondence is possible without domains, has implications for models of analogical reasoning as well as schema induction and inference.
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  69. Conway, C., Goldstone, R. L., & Christiansen, M. (2007). Spatial constraints on visual statistical learning of multi-element displays. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. (pp. 185-190). Nashville, TN: Cognitive Science Society.
    Perception
    Visual statistical learning allows observers to extract high-level structure from visual scenes (Fiser & Aslin, 2001). Previous work has explored the types of statistical computations afforded but has not addressed to what extent learning results in unbound versus spatially bound representations of element cooccurrences. We explored these two possibilities using an unsupervised learning task with adult participants who observed complex multi-element scenes embedded with consistently paired elements. If learning is mediated by unconstrained associative learning mechanisms, then learning the element pairings may depend only on the co-occurrence of the elements in the scenes, without regard to their specific spatial arrangements. If learning is perceptually constrained, cooccurring elements ought to form perceptual units specific to their observed spatial arrangements. Results showed that participants learned the statistical structure of element cooccurrences in a spatial-specific manner, showing that visual statistical learning is perceptually constrained by spatial grouping principles.
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  70. Gerganov, A., Grinberg, M., Quinn, P. C., & Goldstone, R. L. (2007). Simulating conceptually-guided perceptual learning. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. (pp. 287-292). Nashville, TN: Cognitive Science Society.
    Perception
    Visual statistical learning allows observers to extract high-level structure from visual scenes (Fiser & Aslin, 2001). Previous work has explored the types of statistical computations afforded but has not addressed to what extent learning results in unbound versus spatially bound representations of element cooccurrences. We explored these two possibilities using an unsupervised learning task with adult participants who observed complex multi-element scenes embedded with consistently paired elements. If learning is mediated by unconstrained associative learning mechanisms, then learning the element pairings may depend only on the co-occurrence of the elements in the scenes, without regard to their specific spatial arrangements. If learning is perceptually constrained, cooccurring elements ought to form perceptual units specific to their observed spatial arrangements. Results showed that participants learned the statistical structure of element cooccurrences in a spatial-specific manner, showing that visual statistical learning is perceptually constrained by spatial grouping principles.
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  71. Hills, T., Todd, P., & Goldstone, R. L. (2007). Priming and conservation between spatial and cognitive search. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. (359-364). Nashville, TN: Cognitive Science Society.
    Perception
    Visual statistical learning allows observers to extract high-level structure from visual scenes (Fiser & Aslin, 2001). Previous work has explored the types of statistical computations afforded but has not addressed to what extent learning results in unbound versus spatially bound representations of element cooccurrences. We explored these two possibilities using an unsupervised learning task with adult participants who observed complex multi-element scenes embedded with consistently paired elements. If learning is mediated by unconstrained associative learning mechanisms, then learning the element pairings may depend only on the co-occurrence of the elements in the scenes, without regard to their specific spatial arrangements. If learning is perceptually constrained, cooccurring elements ought to form perceptual units specific to their observed spatial arrangements. Results showed that participants learned the statistical structure of element cooccurrences in a spatial-specific manner, showing that visual statistical learning is perceptually constrained by spatial grouping principles.
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  72. Landy, D. & Goldstone, R. L. (2007). How abstract is symbolic thought? Journal of Experimental Psychology: Learning, Memory, & Cognition, 33, 720-733.
    Learning Perception
    In 4 experiments, the authors explored the role of visual layout in rule-based syntactic judgments. Participants judged the validity of a set of algebraic equations that tested their ability to apply the order of operations. In each experiment, a nonmathematical grouping pressure was manipulated to support or interfere with the mathematical convention. Despite the formal irrelevance of these grouping manipulations, accuracy in all experiments was highest when the nonmathematical pressure supported the mathematical grouping. The increase was significantly greater when the correct judgment depended on the order of operator precedence. The result that visual perception impacts rule application in mathematics has broad implications for relational reasoning in general. The authors conclude that formally symbolic reasoning is more visual than is usually proposed.
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  73. Landy, D. & Goldstone, R. L. (2007). The alignment of ordering and space in arithmetic computation. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. (pp. 437-442). Nashville, TN: Cognitive Science Society.
    Learning Perception
    In 4 experiments, the authors explored the role of visual layout in rule-based syntactic judgments. Participants judged the validity of a set of algebraic equations that tested their ability to apply the order of operations. In each experiment, a nonmathematical grouping pressure was manipulated to support or interfere with the mathematical convention. Despite the formal irrelevance of these grouping manipulations, accuracy in all experiments was highest when the nonmathematical pressure supported the mathematical grouping. The increase was significantly greater when the correct judgment depended on the order of operator precedence. The result that visual perception impacts rule application in mathematics has broad implications for relational reasoning in general. The authors conclude that formally symbolic reasoning is more visual than is usually proposed.
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  74. Landy, D. & Goldstone, R. L. (2007). How space guides interpretation of a novel mathematical system. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. (pp. 431-436). Nashville, TN: Cognitive Science Society.
    Learning Perception
    This paper investigates how people build interpretations of compound expressions in a novel formal system. In traditional arithmetic, interpretations are guided by an order of precedence convention (times and division precede addition and subtraction). This order is supported by alignment with the order of precedence. In the experiment described here, participants learned computation tables of two simple novel operators, and then were asked to discover a precedence order between them. The operators were presented with a physical spacing convention that either aligned with the precedence order, opposed it, or randomly opposed or aligned with the precedence order. Participants were more likely to reach a criterion of successful performance when the order of operations aligned with the precedence order, and did so more quickly than either other group. The results indicate that reasoners integrate salient perceptual cues with formal knowledge following particular conventions, even on novel systems.
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  75. Landy, D. & Goldstone, R. L. (2007). Grounding symbol structures in space: Formal notations as diagrams. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. (pp. 425-430). Nashville, TN: Cognitive Science Society.
    [Winner of the 2007 Marr Prize for Best Student Paper at the 2007 Meeting of the Cognitive Science Society]
    Learning Perception
    Although a general sense of the magnitude, quantity, or numerosity is common both in untrained people and animals, the abilities to deal exactly with large quantities and to reason precisely in complex but well-specified situations—to behave formally, that is—are skills unique to people trained in symbolic notations. These symbolic notations employ typically complex, hierarchically embedded structures, which all extant analyses assume are the product of concatenative, rule-based processes. The primary goal of this article is to establish, using behavioral measures on naturalistic tasks, that the some of the same cognitive resources involved in representing spatial relations and proximities are also involved in representing symbolic notations. In short, formal notations are used as a kind of diagram. We examine selfgenerated productions in the domains of handwritten arithmetic expressions and typewritten statements in a formal logic. In both tasks, we find substantial evidence for spatial processes even in these highly symbolic domains.
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  76. Son, J. Y., Smith, L. B., & Goldstone, R. L. (2007). Re-representation using labels: Comparison or replacement. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. (pp. 677-682). Nashville, TN: Cognitive Science Society.
    Learning
    The practice of labeling seems to allow children to make difficult relational similarity matches. Two experiments explore the cognitive processes of comparison and replacement that have been implicated in the beneficial effects of linguistic labeling. Since linguistic labels may be implicated in a number of these processes, our experiments used traditional non-linguistic labels (post-its) to promote either the process of comparison or replacement. Results from two relational matching tasks suggest that comparison is more influential than replacement.
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  77. Son, J. Y., Smith, L. B., & Goldstone, R. L. (2007). Words that evoke schemas: The need for optimal vagueness. Proceedings of the Workshop on Analogies: Integrating Multiple Cognitive Abilities (AnICA07). Nashville, Tennesse.
    Learning
    Although young children typically have trouble reasoning relationally, they are aided by the presence of relational words (e.g., Gentner & Rattermann, 1991) and can reason well about commonly experienced event structures (e.g., Fivush, 1984). Two experiments examine how schema-evoking words help preschool-aged children generalize relational patterns. Experiment 1 shows the superiority of schema-evoking words and Experiment 2 further reveals that these words must be applied to vaguely related events in order to draw attention to structure.
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  78. Goldstone, R. L., & Leydesdorff, L. (2006). The import and export of Cognitive Science. Cognitive Science, 30, 983-993.
    Collective
    From its inception, a large part of the motivation for Cognitive Science has been the need for an interdisciplinary journal for the study of minds and intelligent systems. In the inaugural editorial for the journal, Allan Collins (1977) wrote “Current journals are fragmented along old disciplinary lines, so there is no common place for workers who approach these problems from different disciplines to talk to each other” (p. 1). The interdisciplinarity of the journal has served a valuable cross-fertilization function for those who read the journal to discover articles written for and by practitioners across a wide range of fields. The challenges of building and understanding intelligent systems are sufficiently large that they will most likely require the skills of psychologists, computer scientists, philosophers, educators, neuroscientists, and linguists collaborating and coordinating their efforts.
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    Visit the journal annex for supplemental figures

  79. Janssen, M. A., & Goldstone, R. L. (2006). Dynamic-persistence of cooperation in public good games when group size is dynamic. Journal of Theoretical Biology, 234, 134-142.
    Collective
    The evolution of cooperation is possible with a simple model of a population of agents that can move between groups. The agents play public good games within their group. The relative fitness of individuals within the whole population affects their number of offspring. Groups of cooperators evolve but over time are invaded by defectors which eventually results in the group’s extinction. However, for small levels of migration and mutation, high levels of cooperation evolve at the population level. Thus, evolution of cooperation based on individual fitness without kin selection, indirect or direct reciprocity is possible. We provide an analysis of the parameters that affect cooperation, and describe the dynamics and distribution of population sizes over time.
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  80. Gureckis, T. M., & Goldstone, R. L. (2006). Thinking in groups. Pragmatics and Cognition, 14, 293-311
    Collective Complex
    Is cognition an exclusive property of the individual or can groups have a mind of their own? We explore this question from the perspective of complex adaptive systems. One of the principle insights from this line of work is that rules that govern behavior at one level of analysis (the individual) can cause qualitatively different behavior at higher levels (the group). We review a number of behavioral studies from our lab that demonstrate how groups of people interacting in real-time can self-organize into adaptive, problem-solving group structures. A number of principles are derived concerning the critical features of such “distributed” information processing systems. We suggest that while cognitive science has traditionally focused on the individual, cognitive processes may manifest at many levels including the emergent group-level behavior that results from the interaction of multiple agents and their environment.
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  81. Roberts, M. E., & Goldstone, R. L. (2006). EPICURE: Spatial and Knowledge Limitations in Group Foraging. Adaptive Behavior, 14, 291-313.
    Collective Complex
    We propose an agent-based model of group foraging, EPICURE, for patchily distributed resources. Each agent makes probabilistic movement decisions in a gridworld through a linear combination of current perceptual information and a reinforcement history. EPICURE captures the empirical results from several foraging conditions in Goldstone and Ashpole (2004) and Goldstone, Ashpole, and Roberts (2005), and it leads to a re-evaluation of findings from those papers. In particular, human foragers show contingent usage of information, initially using social information to discover resource pools before private sampling information has been established. We describe a series of simulations that test the sources of resource undermatching often found in group foraging experiments. After testing the effects of foragers’ starting locations, travel costs, the number of foragers, and the size of uniform food distributions, we discuss a novel hypothesis for undermatching. Spatial constraints lead to inadequate individual and group information sampling and cause group undermatching. The foraging group size, food rate, spatial distribution of food, and resulting forager reinforcement histories interact to produce undermatching, and occasionally overmatching, to resources.
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  82. Quinn, P. C., Schyns, P. G., & Goldstone, R. L. (2006). The interplay between perceptual organization and categorization in the representation of complex visual patterns by young infants. Journal of Experimental Child Psychology, 95, 116-127.
    Concepts Perception
    The relation between perceptual organization and categorization processes in 3- and 4-month-olds was explored. The question was whether an invariant part abstracted during category learning could interfere with Gestalt organizational processes. A 2003 study by Quinn and Schyns had reported that an initial category familiarization experience in which infants were presented with visual patterns consisting of a pacman shape and a complex polygon could interfere with infants’ subsequent good continuationbased parsing of a circle from visual patterns consisting of a circle and a complex polygon. However, an alternative noninterference explanation for the results was possible because the pacman had been presented with greater frequency and duration than had the circle. The current study repeated Quinn and Schyns’s procedure but provided an equivalent number of familiarization trials and duration of study time for the infants to process the pacman during initial familiarization and the circle during subsequent familiarization. The results replicated the previous Wndings of Quinn and Schyns. The data are consistent with the interference account and suggest that a cognitive system of adaptable feature creation can take precedence over organizational principles with which a perceptual system comes preequipped.
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  83. Corneille, O., Goldstone, R. L., Queller, S., & Potter, T. (2006). Asymmetries in categorization, perceptual discrimination, and visual search for reference and non-reference exemplars. Memory & Cognition ,34, 556-567.
    Perception
    Two studies examined the representation, treatment, and attention, devoted to the members of reference (i.e., Club members) and non-reference (i.e., Not-Club members) categories. Consistent with prior work on category interrelatedness (e.g. Goldstone, 1996; Goldstone, Steyvers, & Rogosky, 2003), the findings reveal the existence of asymmetric representations for reference and non-reference categories which, however, decreased as expertise and familiarity with the categories increased (Experiment 1 and Experiment 2). Participants also more readily judged two reference than two non-reference exemplars as being the same (Experiment 1), and were better at detecting reference than non-reference exemplars in a set of novel, category-unspecified,exemplars (Experiment 2). These findings provide evidence for the existence of a feature asymmetry in the representation and treatment of exemplars from reference and non-reference categories. Membership in a reference category acts as a salient feature, thereby increasing the perceived similarity and detection of faces that belong in the reference, compared to nonreference, category.
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  84. Goldstone, R. L. (2006). The Complex systems see-change in education. The Journal of Learning Sciences, 15, 35-43.
    Complex Learning
    The day when scientists have time to read broadly across chemistry, biology, physics and social sciences is long gone. Journals, conferences, and academic departmental structures are becoming increasingly specialized and myopic. As Peter Csermely (1999), one of the organizers of the International Forum of Young Scientists expresses it, “There is only a limited effort to achieve the appropriate balance between the discovery of new facts and finding their appropriate place and importance in the framework of science. Science is not self-integrating, and there are fewer and fewer people taking responsibility for ‘net-making” (p. 1621). One possible response to this fragmentation of science is to simply view it as inevitable. Horgan (1996) argues that the age of fundamental scientific theorizing and discoveries has passed, and that all that is left to be done is refining the details of theories already laid down by the likes of Einstein, Darwin, and Newton. Complex systems researchers, and learning scientists more generally, offer an alternative perspective, choosing to reverse the trend toward increasing specialization.
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  85. Goldstone, R. L., Jones, A., & Roberts, M. E. (2006). Group path formation. IEEE Transactions on System, Man, and Cybernetics, Part A, 36, 611-620.
    Collective Complex
    When people make choices within a group, they are frequently influenced by the choices made by others. We have experimentally explored the general phenomenon of group behavior where an early action facilitates subsequent actions. Our concrete instantiation of this problem is group path formation where people travel between destinations with the travel cost for moving onto a location inversely related to the frequency with which others have visited the location. We compare the resulting paths to optimal solutions [Minimal Steiner Trees (MSTs)] and the "Active Walker" model of pedestrian motion from biophysics. There were systematic deviations from beeline pathways in the direction of MST. These deviations showed asymmetries (people took different paths from A to B than they did from B to A) and varied as a function of the topology of the destinations, the duration of travel, and the absolute scale of the world. The Active Walker model accounted for many of these results, in addition to correctly predicting the approximate spatial distribution of steps.
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  86. Goldstone, R. L., & Roberts, M. E. (2006). Self-organized trail systems in groups of humans. Complexity, 11, 43-50.
    Collective Complex
    We have developed an experimental platform for studying the trail systems that spontaneously emerge when people are motivated to take advantage of the trails left by others. In this virtual environment, the participants’ task is to reach randomly selected destinations whileminimizing travel costs. The travel cost of every patch in the environment is inversely related to the number of times the patch was visited by others. The resulting trail systems are a compromise between people going to their destinations and going where many people have previously traveled. We compare the results from our group experiments to the Active Walker model of pedestrian motion from biophysics. The ActiveWalker model accounted for deviations of trails from the beeline paths, the gradual merging of trails over time, and the influences of scale and configuration of destinations on trail systems, as well as correctly predicting the approximate spatial distribution of people’s steps. Two deviations of the model from empirically obtained results were corrected by (1) incorporating a distance metric sensitive to canonical horizontal and vertical axes, and (2) increasing the influence of a trail’s travel cost on an agent’s route as the agent approaches its destination.
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  87. Roberts, M., & Goldstone, R. L. (2006). EPICURE: An agent-based foraging model. Artificial Life X: Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems. Cambridge, MA: MIT Press (379-385).
    Collective
    We present an agent-based foraging model, EPICURE, which captures the results from recent human group foraging experiments (Goldstone and Ashpole, 2004; Goldstone et al., 2005), provides a novel explanation for those results and previous animal foraging results, and makes predictions for future foraging experiments. We describe a series of simulations that test the sources of resource undermatching often found in group foraging experiments. We conclude that foraging group size, food rate, and spatial distribution of food interact to produce undermatching, and occasionally, overmatching, to resources. Furthermore, we present wealth distribution results from the aforementioned empirical studies and EPICURE simulations.
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    Use the simulation described in this paper

  88. Son, J. Y., Smith, L. B., & Goldstone, R. L. (2006). Generalizing from simple instances: An uncomplicated lesson from kids learning objects categories. Proceedings of the Twenty-eighth Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (2174-2179)
    Learning Perception
    Abstraction is the process of stripping away irrelevant information so that learners can generalize on relevant similarities. Can we shortcut this process by directly teaching abstractions in the form of simplified instances? We tested this prediction in the domain of shape-based generalization and found that young children were able to generalize better when taught with simplified shapes rather than complex detailed ones. Simplicity during training allowed shape novices to generalize like shape experts.
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  89. Landy, D., & Goldstone, R. L. (2005). How we learn about things we don't already understand. Journal of Experimental and Theoretical Artificial Intelligence, 17, 343-369.
    Concepts Learning Perception
    The computation-as-cognition metaphor requires that all cognitive objects are constructed from a fixed set of basic primitives; prominent models of cognition and perception try to provide that fixed set. Despite this effort, however, there are no extant computational models that can actually generate complex concepts and processes from simple and generic basic sets, and there are good reasons to wonder whether such models may be forthcoming. We suggest that one can have the benefits of computationalism without a commitment to fixed feature sets, by postulating processes that slowly develop special-purpose feature languages, from which knowledge is constructed. This provides an alternative to the fixed-model conception without radical anti-representationlism. Substantial evidence suggests that such feature development adaptation actually occurs in the perceptual learning that accompanies category learning. Given the existence of robust methods for novel feature creation, the assumption of a fixed basis set of primitives as psychologically necessary is at best premature. Methods of primitive construction include (a) perceptual sensitization to physical stimuli, (b) unitization and differentiation of existing (non-psychological) stimulus elements into novel psychological primitives, guided by the current set of features, and (c) the intelligent selection of novel inputs, which in turn guides the automatic construction of new primitive concepts. Modeling the grounding of concepts as sensitivity to physical properties reframes the question of concept construction from the generation of an appropriate composition of sensations, to the tuning of detectors to appropriate circumstances.
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  90. Hockema, S. A., Blair, M. R., & Goldstone, R. L. (2005). Differentiation for novel dimensions. Proceedings of the Twenty-seventh Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 953-958)
    Perception
    Two experiments are reported that provide evidence for perceptual differentiation between a pair of novel, integral dimensions, in contrast to previous attempts that failed to differentiate these same two dimensions (Op de Beeck,Wagemans, & Vogels, 2003). In Experiment 1, an acquired distinctiveness effect was created on the category-relevant dimension through a categorization training regimen that gradually increased in difficulty. Response times for correct trials were faster across the category boundary. This effect was replicated in Experiment 2 using a new training procedure where participants had to predict category boundaries while watching an animation in which shapes transformed along the category-relevant dimension. Furthermore, the accuracy results of Experiment 2 also indicated that discriminability was changed on the category-relevant dimension relative to the irrelevant dimension across the entire range of the dimension, not just at the category boundary.
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  91. Landy, D., & Goldstone, R. L. (2005). Relational reasoning is in the eyes of the beholder: How global perceptual groups aid and impair algebraic evaluations. Proceedings of the Twenty-seventh Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 2509)
    Learning Perception
    Relational reasoning—reasoning that depends on the interactions of multiple elements, rather than on the intrinsic properties of the elements—is both ubiquitous and challenging. For example, children find it difficult to respond to relational commonalities when object-based similarities are present (Gentner & Rattermann, 1991). Since overt symbol systems such as algebra are external constructs, their terms can contain perceptual regularities. Models of symbolic reasoning, however, typically ignore perceptual regularities (Anderson, in press). It is reasonable to wonder whether people make use of available domaingeneral grouping processes when parsing mathematical structures.

    The purpose of the experiments described here is to evaluate whether algebraic grouping is sensitive to visual grouping. If processing is strictly symbolic, then the manipulation of perceptual regularities should not affect judgments; however, if people use visual grouping to help them parse expressions, then they should make more errors in cases where the perceptual grouping gives an incorrect answer, and be more accurate when visual grouping supports the standard order of operations.
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  92. Mason, W. A., Jones, A., & Goldstone, R. L. (2005). Propagation of innovations in networked groups. Proceedings of the Twenty-seventh Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 1419-1424)
    Collective
    A novel paradigm was developed to study the behavior of groups of networked humans searching a problem space. We examined how different network structures affect the diffusion of information about good solutions. Participants made numerical guesses and received scores that were also made available to their neighbors in the network. When the problem space was monotonic and had only one optimal solution, groups were fastest at finding the solution when all of the groups’ information was presented to them. However, when there were good but suboptimal solutions (i.e., local maxima), the group connected via a small-world network (Watts & Strogatz, 1998) was faster at finding the best solution than all other network structures.
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  93. Roberts, M. E., & Goldstone, R. L. (2005). Explaining resource undermatching with agent-based models. Proceedings of the Twenty-seventh Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 1872-1877)
    Collective
    We propose two agent-based models of group foraging for two perceptual conditions. These models exhibit complex group-level behavior using only a simple rule set with a homogeneous group of agents. The models are shown to replicate results from Goldstone and Ashpole (2004), and we describe a series of simulations that test the sources of the resource undermatching often found in group foraging experiments. After testing the effects of travel costs, the number of agents, and uniform variance food distributions, we conclude that many group foraging studies have overlooked the interplay of spatial constraints with food rates in causing undermatching.
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  94. Son, J. Y., & Goldstone, R. L. (2005). Relational words as handles: They bring along baggage. Proceedings of the Twenty-seventh Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 2050-2055)
    Learning
    Two experiments examined the role of relational language on analogical transfer. Participants were taught Signal Detection Theory (SDT) embedded in a doctor story. In the experimental condition, relational words accompanied the story. Relational words that shared superficial similarity with the contextual elements facilitated transfer. Without the shared semantics, relational words were detrimental to transfer performance. A computational model lends a more structured perspective on how language changes cognition.
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  95. Goldstone, R. L., Rogosky, B. J., Pevtzow, R., & Blair, M. (2005). Perceptual and semantic reorganization during category learning. In H. Cohen & C. Lefebvre (Eds.) Handbook of Categorization in Cognitive Science. (pp. 651-678). Amsterdam: Elsevier.
    Concepts Perception
    Category learning not only depends upon perceptual and semantic representations; it also leads to the generation of these representations. We describe two series of experiments that demonstrate how categorization experience alters, rather than simply uses, descriptions of objects. In the first series, participants first learned to categorize objects on the basis of particular sets of line segments. Subsequently, they were given a perceptual part-whole judgment task. Categorization training influenced participants’ partwhole judgments, indicating that whole objects were more likely to be broken down into parts that were relevant during categorization. In the second series, correlations were created or broken between semantic features of word concepts (e.g., ferocious vs. timid, and group-oriented vs. solitary animals). The best transfer was found between category learning tasks that shared the same semantic organization of concepts. Together, the experiments support models of category learning that simultaneously create the elements of categorized objects’ descriptions and associate those elements with categories.
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  96. Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in Cognitive Science, 9, 424-430.
    Collective Complex
    Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agent-based models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion, and cooperation, and can be used to predict, manipulate, and improve upon collective behavior. ABMs overcome an assumption underlying much of cognitive science – that the individual is the critical unit of cognition. The advocated alternative is that individuals participate in collective organizations that they may not understand or even perceive, and that these organizations affect and are affected by individual behavior.
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  97. Feng, Y., Goldstone, R. L., & Menkov, V. (2005). A Graph Matching Algorithm and its Application to Conceptual System Translation. International Journal on Artificial Intelligence Tools, 14, 77-100.
    Similarity Concepts
    ABSURDIST II, an extension to ABSURDIST, is an algorithm using attributed graph matching to find translations between conceptual systems. It uses information about the internal structure of systems by itself, or in combination with external information about concept similarities across systems. It supports systems with multiple types of weighted or unweighted, directed or undirected relations between concepts. The algorithm exploits graph sparsity to improve computational efficiency.We present the results of experiments with a number of conceptual systems, including artificially constructed random graphs with introduced distortions.
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  98. Goldstone, R. L., Feng, Y., & Rogosky, B. (2005).  Connecting concepts to the world and each other. In D. Pecher & R. Zwaan (Eds.)  Grounding cognition: The role of perception and action in memory, language, and thinking.  Cambridge: Cambridge University Press. (pp. 292-314)
    Similarity Concepts Complex

    How can well tell that two people both have a concept of dog, gold, or car despite differences in their conceptual knowledge?  Two kinds of information can be used to translate between the concepts in two persons’ minds: the internal relations between concepts within each person’s mind, and external grounding of the concepts.  We present a neural network model called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems Themselves) that integrates internal and external determinants of conceptual meaning to find translations across people or other systems.  The model shows that appropriate translations can be found by considering only similarity relations among concepts within a person.  However, simulations also indicate synergistic interactions between internal and external sources of information. ABSURDIST is then applied to analogical reasoning, dictionary translation, translating between web-based ontologies, subgraph matching, and object recognition.  The performance of ABSURDIST suggests the utility of concepts that are simultaneously externally grounded and enmeshed within a conceptual system.
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  99. Rogosky, B. J., & Goldstone, R. L. (2005). Adaptation of perceptual and semantic features. In L. A. Carlson & E. van der Zee (Eds.), Functional features in language and space: Insights from perception, categorization and development. (pp. 257-273). Oxford, England: Oxford University Press.
    Concepts Perception
    This chapter examines the role of feature in theories of concepts, perception, and language. The authors define features as psychological representations of properties in the world that can be processed independently of other properties and that are relevant to a task, such as categorization. They discuss the classic view of features as entities that do not change over time. They argue for an alternative view in which features are created and adapted according to the immediate goals and context of tasks, and over longer time periods in terms of perceptual and conceptual learning and development. The authors also distinguish pairs of dimensions in terms of whether the dimensions can be processed separately (i.e. either dimension can be attended independently of the other) or integrally (i.e. the dimensions cannot be processed independently). They present a study of the classification of linguistic stimuli according to rules based on semantic features (e.g. ferocity and socialness of animals). The results indicate that changes in the integral processing of the dimensions can be induced by tasks that favor the separate processing of one dimenion. The findings support the authors' claim that, like perceptual features, semantic features can be adapted during learning.
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  100. Goldstone, R. L., & Son, J. Y. (2005).  The transfer of scientific principles using concrete and idealized simulations.  The Journal of the Learning Sciences, 14, 69-110.
    Learning Perception

    Participants in two experiments interacted with computer simulations designed to foster understanding of scientific principles governing complex adaptive systems.  The quality of participants’ transportable understanding was measured by the amount of transfer between two simulations governed by the same principle.  The perceptual concreteness of the elements within the first simulation was manipulated.  The elements either remained concrete throughout the simulation, remained idealized, or switched midway into the simulation from concrete to idealized or vice versa.  Transfer was better when the appearance of the elements switched, consistent with theories predicting more general schemas when the schemas are multiply instantiated.  The best transfer was observed when originally concrete elements became idealized.  These results are interpreted in terms of tradeoffs between grounded, concrete construals of simulations and more abstract, transportable construals.  Progressive idealization (“Concreteness fading”) allows originally grounded and interpretable principles to become less tied to specific contexts and hence more transferable.
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  101. Goldstone, R. L, & Son, J. (2005).  Similarity.  In K. Holyoak & R. Morrison (Eds.).  Cambridge Handbook of Thinking and Reasoning.  Cambridge: Cambridge University Press. (pp. 13-36).
    Similarity

    Human assessments of similarity are fundamental to cognition because similarities in the world are revealing.  The world is an orderly enough place that similar objects and events tend to behave similarly.  This fact of the world is not just a fortunate coincidence.  It is because objects are similar that they will tend to behave similarly in most respects.  It is because crocodiles and alligators are similar in their external form, internal biology, behavior, diet, and customary environment that one can often successfully generalize from what one knows of one to the other.  As Quine (1969) observed, “Similarity, is fundamental for learning, knowledge and thought, for only our sense of similarity allows us to order things into kinds so that these can function as stimulus meanings.  Reasonable expectation depends on the similarity of circumstances and on our tendency to expect that similar causes will have similar effects (p. 114).”  Similarity thus plays a crucial role in making predictions because similar things usually behave similarly.
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  102. Goldstone, R. L., Ashpole, B. C., & Roberts, M. E., (2005). Knowledge of resources and competitors in human foraging.  Psychonomic Bulletin & Review, 12, 81-87.
    Collective

    The allocation of human participants to resources was studied by observing the population dynamics of people interacting in real-time within a common virtual world. Resources were distributed in two spatially separated pools with varying relative reinforcement rates (50-50, 65- 35, or 80-20). We manipulated whether participants could see each other and the distribution of resources. When participants could see each other but not the resources, the richer pool was underutilized. When participants could see the resources but not each other, the richer pool was overutilized. In conjunction with prior experiments that correlated the visibility of agents and resources (Goldstone & Ashpole, in press), these results indicate that participants’ foraging decisions are influenced by both forager and resource information. The results suggest that the presence of a crowd at a resource is a deterring rather than attractive factor. Both fast and slow oscillations in the harvesting rates of the pools across time were revealed by Fourier analyses. The slow waves of crowd migration are most prevalent when the resources are invisible, whereas the fast cycles are most prevalent when the resources are visible and participants are invisible.
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  103. Feng, Y., Goldstone, R. L., & Menkov, V (2004).  ABSURDIST II: A Graph Matching Algorithm and its Application to Conceptual System Translation.  FLAIRS 2004.
    Similarity Concepts

    ABSURDIST II, an extension to ABSURDIST, is an algorithm using attributed graph matching to find translations between conceptual systems. It uses information about the internal structure of systems by itself, or in combination with external information about concept similarities across systems. It supports systems with multiple types of weighted or unweighted, directed or undirected relations between concepts. The algorithm exploits graph sparsity to improve computational efficiency. We present the results of experiments with a number of conceptual systems, including artificially constructed random graphs with introduced distortions.
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  104. Börner, K, Maru, J. T., & Goldstone, R. L. (2004).  The simultaneous evolution of article and author networks in PNAS.  The Proceedings of the National Academy of Science, 101, 5266-527.
    Collective Complex

    There has been a long history of research into the structure and evolution of mankind’s scientific endeavor. However, recent progress in applying the tools of science to understand science itself has been unprecedented because only recently has there been access to high-volume and high-quality data sets of scientific output (e.g., publications, patents, grants), as well as computers and algorithms capable of handling this enormous stream of data. This paper reviews major work on models that aim to capture and recreate the structure and dynamics of scientific evolution. We then introduce a general process model that simultaneously grows co-author and paper-citation networks. The statistical and dynamic properties of the networks generated by this model are validated against a 20-year data set of articles published in the Proceedings of the National Academy of Science. Systematic deviations from a power law distribution of citations to papers are well fit by a model that incorporates a partitioning of authors and papers into topics, a bias for authors to cite recent papers, and a tendency for authors to cite papers cited by papers that they have read. In this TARL model (for Topics, Aging, and Recursive Linking), the number of topics is linearly related to the clustering coefficient of the simulated paper citation network.
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  105. Goldstone, R. L. (2004). Believing is seeing. American Psychological Society Observer, 17, 23-26.

    Human concept learning clearly depends upon perception. Our concept of "gerbil" is built out of perceptual features such as "furry," "small," and "four-legged." However, recent research has found that the dependency works both ways. Perception not only influences, but is influenced by, the concepts that we learn. Our laboratory has been exploring the psychological mechanisms by which concepts and perception mutually influence one another, and building computational models to show that the circle of influences is benign rather than vicious.
    Perception
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  106. Goldstone, R. L., & Ashpole, B. C. (2004). Human foraging behavior in a virtual environment. Psychonomic Bulletin & Review, 11, 508-514.
    Collective

    Our goal in this research is to collect a large volume of time-evolving data from a system composed of human agents vying for resources in a common environment, with the eventual aim of guiding the development of computational models of human resource allocation.  We have developed an experimental platform that allows a large number of human participants to interact in real-time within a common virtual world.  Two resource pools were created with different rates of replenishment.  The participants’ task was to obtain as many resource tokens as possible during an experiment.  In addition to varying the relative replenishment rate for the two resources (50-50, 65-35, 80-20), we manipulated whether agents could see each other and the entire food distribution, or had their vision restricted to food in their own location.  As a collective, the agents would optimally harvest the resources if they distribute themselves proportionally to the distribution of resources.  Empirical violations of global optimality were found. First, there was a systematic underutilization of the more preponderant resource.  For example, agents distributed themselves approximately 75% and 25% to resources pools that had relative replenishment rates of 80% and 20%, respectively.  The expected pay-off per agent was larger for pools with relatively high replenishment rates.  Second, there were oscillations in the harvesting rates of the resources across time, particularly when agents’ vision was restricted.  Perceived underutilization of a resource resulted in an influx of agents to that resource.  This sudden influx, in turn, resulted in a glut of agents, which then led to a trend for agents to depart from the resource region.  This cyclic activity in the collective data was revealed by a Fourier analysis showing prominent power in the range of about 50 seconds per cycle.
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  107. Goldstone, R. L. (2003).  Learning to perceive while perceiving to learn.  in R. Kimchi, M. Behrmann, and C. Olson (Eds.) Perceptual Organization in Vision: Behavioral and Neural Perspectives.  Mahwah, New Jersey.  Lawrence Erlbaum Associates. (pp. 233-278)
    Concepts Complex Learning Perception

    The external world must be filtered through our perceptual systems before it can have an impact upon us.  That is, the world we experience is formed by our perceptual processing.  However, it is not viciously circular to argue that our perceptual systems are reciprocally formed by our experiences.  In fact, it is because our experiences are necessarily based on our perceptual systems that these perceptual systems must be shaped so that our experiences are appropriate and useful for dealing with our world.

    In what follows, I will argue that the "building blocks" an observer uses for construing their world depends on the observer’s history, training, and acculturation. These factors, together with psychophysical constraints, mold one’s set of building blocks.  Researchers who have proposed fixed sets of hard-wired primitives are exactly right in one sense -- the combinatorics of objects, words, scenes, and scenarios strongly favor componential representations.  However, this does not necessitate that the components be hard-wired.  By developing new components to subserve particular tasks and environments, a newly important discrimination can generate building blocks that are tailored for the discrimination.  Adaptive building blocks are likely to be efficient because they can be optimized for idiosyncratic needs and environments.

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  108. Goldstone, R. L., Ashpole, B. C. (2003). The distribution of people to resources in a networked multi-player environment.  Proceedings of the 25th Annual Conference of the Cognitive Science Society.

     This is an abridged version of Goldstone & Ashpole (2004).
    Collective
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  109. Goldstone, R. L., & Sakamoto, Y. (2003). The Transfer of Abstract Principles Governing Complex Adaptive Systems.  Cognitive Psychology, 46, 414-466.
    Complex Learning
    Four experiments explored participants' understanding of the abstract principles governing computer simulations of complex adaptive systems.  Experiment 1 revealed better transfer between computer simulations when they were governed by the same abstract principle, even when the simulations' domains were dissimilar.  Experiments 2 and 3 showed better transfer of abstract principles across simulations that were relatively dissimilar, and that this effect was due to participants who performed relatively poorly on the initial simulation.   In Experiment 4, participants showed better abstract understanding of a simulation when it was depicted with concrete rather than idealized graphical elements.  However, for poor performers, the idealized version of the simulation transferred better to a new simulation governed by the same abstraction.  The results are interpreted in terms of competition between abstract and concrete construals of the simulations.  Individuals prone toward concrete construals tend to overlook abstractions when concrete properties or superficial similarities are salient.
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  110. Goldstone, R. L., Steyvers, M., & Rogosky, B. J. (2003). Conceptual interrelatedness and caricatures.  Memory & Cognition, 31, 169-180.
    Concepts
    Concepts are interrelated to the extent that the characterization each concept is influenced by the other concepts, and isolated to the extent that the characterization of one concept is independent of other concepts.  The relative categorization accuracy of the prototype and caricature of a concept can be used as a measure of concept interrelatedness.  The prototype is the central tendency of a concept, whereas a caricature deviates from the concept’s central tendency in the direction opposite to the central tendency of other acquired concepts.  The prototype is predicted to be relatively well categorized when a concept is relatively independent of other concepts, but the caricature is predicted to be relatively well categorized when a concept is highly related to other concepts.  Support for these predictions comes from manipulations of the labels given to simultaneously acquired concepts (Experiment 1) and the order of categories during learning (Experiment 2).
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  111. Goldstone, R. L., & Johansen, M. K. (2003). Conceptual development from origins to asymptotes.  In D. Rakison & L. Oakes (Eds.) Categories and concepts in early development.  (pp. 403-418).  Oxford, England: Oxford University Press.
    Concepts Perception

    Scientists studying adult concept learning are typically careful to analyze the entire pattern of responses given across all of the trials of an experiment.  Often times, the early trials are the most diagnostic because categorization accuracy quickly reaches an asymptote.  We take some pride in tackling the hard problem of accounting for adaptive processes that account for category learning, unlike many psychophysicists, who simply throw out the first 1000 trials because steady-state performance has not yet been reached.  However, lest we grow too smug, the chapters of this book provide a great service by reminding us that even though we analyze the very first trial of our experiment, we are still studying conceptual change that occurs almost imperceptibly close to the asymptote.  By the time that our 20-year-old subjects come to our laboratories, they have learned the majority of the concepts that they will ever learn and virtually all of their truly foundational concepts.  Relatively brief laboratory training suffices to teach students the rule “Circle Above Square” (Bruner, Goodnow, & Austin, 1956), a particular configuration of 9 dots (Posner & Keele, 1968), or a new fact such as that grebes are birds, but this rapid learning is only possible because it builds upon a longer and more profound process by which concepts such as Above (Quinn, this volume), Bird (Mervis, Pani & Pani, this volume), Animal (Mareschal, this volume; Mandler, this volume), and Animacy (Gelman & Koenig, this volume; Rakison, this volume) are learned.

    Those of us who want to develop theories of the learning and representation of adult concepts cannot afford to remain blind to the conceptual development that makes possible adult concept use.  This life-long learning provides us with the fundamental representations that we subsequently combine and tweak.  In assessing the contribution of developmental research on concepts and categories to our general understanding of human concepts, we will ask four questions: what are concepts; what is the relation between perception and concepts; what are the constraints on concept learning; and what are promising future directions for research on concepts?

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  112. Goldstone, R. L., & Kersten, A. (2003). Concepts and Categories. In A. F. Healy & R. W. Proctor (Eds.) Comprehensive handbook of psychology, Volume 4: Experimental psychology.  (pp. 591-621).  New York: Wiley.
    Concepts
    Issues related to concepts and categorization are nearly ubiquitous in psychology because of peoples natural tendency to perceive a thing AS something.  Zen meditation practices may or may not succeed in allowing a person to grasp the object itself rather than the labels and associations it evokes.  In either case, the difficulty of this pursuit affirms the powerful impulse that we have to interpret our world.  This act of interpretation, an act of seeing something as X rather than simply seeing it (Wittgenstein, 1953), is fundamentally an act of categorization.

    The attraction of research on concepts is that an extremely wide variety of cognitive acts can be understood as categorizations.  Identifying the person sitting across from you at the breakfast table involves categorizing something as your spouse.  Diagnosing the cause of someones illness involves a disease categorization.  Interpreting a painting as a Picasso, an artifact as Mayan, a geometry as Non-Euclidean, a fugue as baroque, a conversationalist as charming, a wine as a Bordeaux, and a government as socialist are categorizations at various levels of abstraction.  The typically unspoken assumption of research on concepts is that these cognitive acts have something in common.  That is, there are principles that explain many or all acts of categorization.  This assumption is controversial (see Medin, Lynch, & Solomon, 2000), but is perhaps justified by its potential pay-off.  If there are common principles governing concepts in their diverse manifestations, then discovering these principles would have a tremendous benefit, for we would not only acquire an understanding of how people identify faces, recognize letters, treat diseases, or form categories in a specialized domain.  We would also have a unified understanding of all of these phenomena as examples of a generic process of concept formation.
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  113. Halberstadt, J., Goldstone, R. L., & Levine, G. M. (2003). Featural Processing in Face Preferences.  Journal of Experimental Social Psychology, 39, 270-278.
    Perception
    Two experiments examined how practice and time pressure influence holistic processing, defined as the relative importance of feature interactions, in a face preference task.  Participants rated 32 cartoon faces that varied along five dichotomous features (Experiment 1) or 27 realistic morphed faces that varied along three trichotomous dimensions (Experiment 2), under high and low time pressure (operationalized as a short versus long stimulus presentation time), over a series of experimental blocks. In both experiments, the overall importance of facial features, but not of feature interactions, increased over blocks and, in one condition of Experiment 1, under high versus low time pressure.  Analyses of idiosyncratic importance indicated that the feature effects were due to the increasing importance of participants' idiosyncratically most influential features.  Functional differences between face preferences and face recognition are offered to explain and predict when facial features will be processed independently versus holistically.
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  114. Shyi, G. S. -W., Goldstone, R. L., Hummel, J. E., & Lin, C. (submitted). Computing representations for bound and unbound object matching.
    Perception
    Five experiments examined the nature of object representation. Participants made same-different judgments between two multipart 3-D objects, according to rules where either the object parts and their spatial relationship had to be considered (role-relevant, RR) or just the object parts (role-irrelevant, RI). Results indicate that it was easiest to judge two identical and orientationally aligned objects according to either rule, followed by judging those that shared identical parts located in different positions according to the RI rule. It was most difficult to judge the latter according to the RR rule when they were misaligned by rotation. These findings lend support to the hypothesis that object representations at the image level, part level, or full structural description level may be computed and used for making same-different judgements. The implications of our findings for object recognition in general and the role of spatial attention in particular are discussed.
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  115. Goldstone, R. L., & Rogosky, B. J. (2002). Using relations within conceptual systems to translate across conceptual systems, Cognition, 84, 295-320.
    Similarity Concepts Complex
    We explore one aspect of meaning, the identification of matching concepts across systems (e.g. people, theories, or cultures).  We present a computational algorithm called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation) that uses only within-system similarity relations to find between-system translations.  While illustrating the sufficiency of within-system relations to account for translating between systems, simulations of ABSURDIST also indicate synergistic interactions between intrinsic, within-system information and extrinsic information.
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    Here is a brief description and commentary on ABSURDIST:
    Dietrich, E. (2003).  An ABSURDIST model vindicates a venerable theory.  Trends in Cognitive Science, 7, 57-59.
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  116. Goldstone, R. L., & Rogosky, B. J. (2002). The role of roles in translating across conceptual systems, Proceedings of the Twenty-fourth Annual Conference of the Cognitive Science Society.  Hillsdale, New Jersey: Lawrence Erlbaum Associates.  (pp. 369-374).
    Similarity Concepts Complex
    According to an “external grounding” theory of meaning, a concept’s meaning depends on its connection to the external world.  By a “conceptual web” account, a concept’s meaning depends on its relations to other concepts within the same system.  We explore one aspect of meaning, the identification of matching concepts across systems (e.g. people, theories, or cultures).  We present a computational algorithm called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation) that uses only within-system similarity relations to find between-system translations.  While illustrating the sufficiency of a conceptual web account for translating between systems, simulations of ABSURDIST also indicate powerful synergistic interactions between intrinsic, within-system information and extrinsic information.  Applications of the algorithm to issues in object recognition, shape analysis, automatic translation, human analogy and comparison making, pattern matching, neural network interpretation, and statistical analysis are described.
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  117. Goldstone, R. L, Lippa, Y., & Shiffrin, R. M. (2001). Altering object representations through category learning.  Cognition, 78, 27-43.
    Concepts Perception
    Previous research has shown that objects that are grouped together in the same category become more similar to each other and that objects that are grouped in different categories become increasingly dissimilar, as measured by similarity ratings and psychophysical discriminations. These findings are consistent with two theories of the influence of concept learning on similarity. By a strategic judgment bias account, the categories associated with objects are explicitly used as cues for determining similarity, and objects that are categorized together are judged to be more similar because similarity is not only a function of the objects themselves, but also the objectsí category labels. By a representational change account, category learning alters the description of the objects themselves, emphasizing properties that are relevant for categorization. A new method for distinguishing between these accounts is introduced which measures the difference between the similarity ratings of categorized objects to a neutral object. The results indicate both strategic biases based on category labels and genuine representational change, with the strategic bias affecting mostly objects belonging to different categories and the representational change affecting mostly objects belonging to the same category.
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  118. Goldstone, R. L, & Steyvers, M. (2001). The Sensitization and Differentiation of Dimensions During Category Learning.  Journal of Experimental Psychology: General, 130,116-139.
    Similarity Concepts Perception
    The reported experiments explore two mechanisms by which object descriptions are flexibly adapted to support concept learning: selective attention and dimension differentiation. Arbitrary dimensions were created by blending photographs of faces in different proportions, and mixing these blends together.  Consistent with learned selective attention, positive transfer was found when initial and final categorizations shared either relevant or irrelevant dimensions, and negative transfer was found when previously relevant dimensions became irrelevant. Unexpectedly good transfer was observed when both irrelevant dimensions became relevant and relevant dimensions became irrelevant, and was explained in terms of participants learning to isolate one dimension from another. This account was further supported by experiments indicating that conditions expected to produce positive transfer via dimension differentiation produced better transfer than conditions expected to produce positive transfer via selective attention, but only when stimuli were composed of highly integral and overlapping dimensions. We discuss the relation between dimension differentiation and selective attention, mechanisms that may underlie these processes, and implications for category learning research.
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  119. Lippa, Y., & Goldstone, R. L. (2001).  The Acquisition of Automatic Response Biases through Stimulus-Response Mapping and Categorization Determined by a Compatibility Task.  Memory & Cognition,  29, 1051-1060
    Concepts Perception
    Experiments explored whether spatially neutral stimuli acquire the ability to automatically elicit spatial responses. In Experiment 1, participants associated line-drawings with either left or right key presses. Subsequently, the pictures were used in a Simon task wherein participants made left and right key presses based on the color of the picture, ignoring its shape. Participants responded more quickly when the key press previously associated with the picture matched, rather than mismatched, the response required by the picture's color. In Experiment 2, participants learned response categories that grouped spatially ambiguous line-drawings together with pictures of left- and right-pointing arrows and fingers. A subsequent Simon task again yielded compatibility effects, indicating that the spatially ambiguous pictures inherited the response biases of the other objects in their category. Thus, responses directly associated with shapes, and indirectly associated with shapes by category membership, are both automatically triggered even when the responses are irrelevant and inappropriate.
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  120. Goldstone, R. L. (2000). Unitization during Category Learning.  Journal of Experimental Psychology: Human Perception and Performance, 26, 86-112
    Concepts Perception
    Five experiments explored the question of whether new perceptual units can be developed if they are diagnostic for a category learning task, and if so, what are the constraints on this unitization process? During category learning, participants were required to attend either a single component or a conjunction of five components in order to correctly categorize an object. In Experiments 1-4, some evidence for unitization was found in that the conjunctive task becomes much easier with practice, and this improvement was not found for the single component task, or for conjunctive tasks where the components cannot be unitized. Influences of component order (Experiment 1), component contiguity (Experiment 2), component proximity (Experiment 3), and number of components (Experiment 4) on practice effects were found. Using a Fourier Transformation method for deconvolving response times (Experiment 5), prolonged practice effects yielded responses that were faster than expected by analytic model that integrate evidence from independently perceived components.
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  121. Goldstone, R. L. (2000). A neural network model  of concept-influenced segmentation.  Proceedings of the Twenty-second Annual Conference of the Cognitive Science Society.  Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 172-177).
    Perception
    Several models of categorization assume that fixed perceptual representations are combined together to determine categorizations.  This research explores the possibility that categorization experience alters, rather than simply uses, descriptions of objects.  Based on results from human experiments, a  model is presented in which a competitive learning network is first given categorization training, and then is given a subsequent segmentation task, using the same network weights.  Category learning establishes detectors for stimulus parts that are diagnostic, and these detectors, once established, bias the interpretation of subsequent objects to be segmented.
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  122. Goldstone, R. L., Steyvers, M., Spencer-Smith, J., & Kersten, A. (2000). Interactions between perceptual and conceptual learning. in E. Diettrich & A. B.  Markman (eds.) Cognitive Dynamics: Conceptual Change in Humans and Machines.  Mahwah, New Jersey: Lawrence Erlbaum Associates.  (pp. 191-228).
    Concepts Perception
    Confusions arise when 'stable' is equated with 'foundational.' Spurred on by the image of a house`s foundation, it is tempting to think that something provides effective support to the extent that it is rigid and stable. We will argue that when considering the role of perception in grounding our concepts, exactly the opposite is true. Our perceptual system supports our ability to acquire new concepts by being flexibly tuned to these concepts. Whereas the concepts that we learn are certainly influenced by our perceptual representations, we will argue that these perceptual representations are also influenced by the learned concepts. In keeping with one of the central themes of this book, behavioral adaptability is completely consistent with representationalism. In fact, the most straightforward account of our experimental results is that concept learning can produce changes in perceptual representations, the 'vocabulary' of perceptual features, that are used by subsequent tasks.

    This chapter reviews theoretical and empirical evidence that perceptual vocabularies used to describe visual objects are flexibly adapted to the demands of their user. We will extend arguments made elsewhere for adaptive perceptual representations (Goldstone, Schyns, & Medin, in press; Schyns, Goldstone, & Thibaut, in press), and discuss research from our laboratory illustrating specific interactions between perceptual and conceptual learning. We will describe computer simulations that provide accounts of these interactions using neural network models. These models have detectors that become increasingly tuned to the set of perceptual features that support concept learning. The bulk of the chapter will be organized around mechanisms of human perceptual learning, and computer simulations of these mechanisms.
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  123. Goldstone, R. L. (1999). Similarity. in R.A. Wilson & F. C. Keil (eds.) MIT encylopedia of the cognitive sciences.(pp. 763-765).Cambridge, MA: MIT Press
    Similarity
    An ability to assess similarity lies close to the core of cognition. In the time-honored tradition of legitimizing fields of psychology by citing William James, `This sense of Sameness is the very keel and backbone of our thinking` (James, 1890/1950; p. 459). Similarity plays an indispensable foundational role in theories of cognition. People`s success in problem solving depends on the similarity of previously solved problems to current problems. Categorization depends on the similarity of objects to be categorized to category members. Memory retrieval depends on the similarity of retrieval cues to stored memories. Inductive reasoning is based on the principle that if an event is similar to a previous event, then similar outcomes are predicted. An understanding of these cognitive processes requires that we understand how humans assess similarity. Four major psychological models of similarity are: geometric, featural, alignment-based, and transformational.
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  124. Goldstone, R. L. (1998). Perceptual Learning.  Annual Review of Psychology, 49, 585-612.
    Perception
    Perceptual learning involves relatively long-lasting changes to an organism`s perceptual system that improve its ability to respond to its environment. Four mechanisms of perceptual learning are discussed: attention weighting, imprinting, differentiation, and unitization. By attention weighting, perception becomes adapted to tasks and environments by increasing the attention paid to important dimensions and features. By imprinting, receptors are developed that are specialized for stimuli or parts of a stimuli. By differentiation, stimuli that were once indistinguishable become psychologically separated. By unitization, tasks that originally required detection of several parts come to be accomplished by detecting a single constructed unit representing a complex configuration. Research from cognitive psychology, psychophysics, neuroscience, expert/novice differences, development, computer science, and cross-cultural differences is described that relates to these mechanisms. The locus, limits, and applications of perceptual learning are also discussed.
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  125. Goldstone, R. L. (1998). Hanging Together: A connectionist model of similarity. In J. Grainger & A. M. Jacobs (Eds.)  Localist Connectionist Approaches to Human Cognition.  (pp. 283 - 325).  Mahwah, NJ: Lawrence Erlbaum Associates.
    Similarity Complex
    Human judgments of similarity have traditionally been modelled by measuring the distance between the compared items in a psychological space, or the overlap between the items` featural representations. An alternative approach, inspired jointly by work in analogical reasoning (D. Gentner, 1983; K. T. Holyoak & P. Thagard, 1989) and interactive activation models of perception (J. L. McClelland & D. E. Rumelhart, 1981), views the process of judging similarity as one of establishing alignments between the parts of compared entities. A localist connectionist model of similarity, SIAM, is described wherein units represent correspondences between scene parts, and these units mutually and concurrently influence each other according to their compatability. The model is primarily applied to similarity rating tasks, but is also applied to other indirect measures of similarity, to judgments of alignment between scene parts, to impressions of comparison difficulty, and to patterns of perceptual sensitivity for matching and mismatching features.
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  126. Goldstone, R. L., & Barsalou, L. (1998). Reuniting perception and conception. Cognition, 65, 231-262.
    Concepts Perception
    (reprinted as
    : Goldstone, R. L., & Barsalou, L. (1998).  Reuniting perception and conception.  In S. A. Sloman and L. J. Rips (Eds.) Similarity and symbols in human thinking.  (pp. 145-176).  Cambridge, MA: MIT Press)
    Work in philosophy and psychology has argued for a dissociation between perceptually-based similarity and higher-level rules in conceptual thought. Although such a dissociation may be justified at times, our goal is to illustrate ways in which conceptual processing is grounded in perception, both for perceptual similarity and abstract rules. We discuss the advantages, power, and influences of perceptually-based representations. First, many of the properties associated with amodal symbol systems (e.g. productivity and generativity) can be achieved with perceptually-based systems as well. Second, relatively raw perceptual representations are powerful because they can implicitly represent properties in an analog fashion. Third, perception naturally provides impressions of overall similarity, exactly the type of similarity useful for establishing many common categories. Fourth, perceptual similarity is not static but becomes tuned over time to conceptual demands. Fifth, the original motivation or basis for sophisticated cognition is often less sophisticated perceptual similarity. Sixth, perceptual simulation occurs even in conceptual tasks that have no explicit perceptual demands. Parallels between perceptual and conceptual processes suggest that many mechanisms typically associated with abstract thought are also present in perception, and that perceptual processes provide useful mechanisms that may be coopted by abstract thought.
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  127. Kersten, A. W., Goldstone, R. L., & Schaffert, A.(1998). Two Competing Attentional Mechanisms in Category Learning.Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 1437-1458.
    Concepts Perception
    This research provides evidence for two competing attentional mechanisms. Attentional persistence directs attention to attributes previously found to be predictive, whereas contrast directs attention to stimuli that have not already been associated with a category. Three experiments provide evidence for these mechanisms. Experiments 1 and 2 revealed increased attention to an attribute following training in which that attribute was relevant, providing evidence for persistence. These experiments also revealed increased attention to an attribute following training in which another, more salient attribute was relevant, providing evidence for contrast. Experiment 3 used a subtractive method to determine the contributions of persistence and contrast to changes in attention to an attribute. The results suggest that persistence operates primarily at the level of dimensions, whereas contrast operates at the level of dimension values.
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  128. Schyns, P. G., Goldstone, R. L., & Thibaut, J-P (1998). Development of features in object concepts.  Behavioral and Brain Sciences, 21, 1-54.
    Concepts Perception
    According to an influential approach to cognition, our perceptual systems provide us with a repertoire of fixed features as input to higher-level cognitive processes. We present a theory of category learning and representation in which features, instead of being components of a fixed repertoire, are created under the influence of higher-level cognitive processes. When new categories need to be learned, fixed features face one of two problems: (1) High-level features that are directly useful for categorization may not be flexible enough to represent all relevant objects. (2) Low-level features consisting of unstructured fragments (such as pixels) may not capture the regularities required for successful categorization. We report evidence that feature creation occurs in category learning and we describe the conditions that promote it. Feature creation can adapt flexibly to changing environmental demands and may be the origin of fixed feature repertoires. Implications for object categorization, conceptual development, chunking, constructive induction and formal models of dimensionality reduction are discussed.
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  129. Schyns, P. G., Goldstone, R. L., & Thibaut, J. (1998).  Ways of featuring in object categorization.  Behavioral and Brain Sciences, 21, 41-49.  (response to commentaries).
    Concepts Perception

  130. Goldstone, R. L., Medin, D. L., & Halberstadt, J. (1997) Similarity in Context.. Memory & Cognition, 25, 237-255
     
    Similarity
    Similarity comparisons are highly sensitive to judgment context. Three experiments explore context effects that occur within a single comparison rather than across several trials. Experiment 1 shows reliable intransitivities in which a target is judged to be more similar to stimulus A than to stimulus B, more similar to B than to stimulus C, and more similar to C than to A. Experiment 2 explores the locus of Tversky`s (1977) diagnosticity effect in which the relative similarity of two alternatives to a target is influenced by a third alternative. Experiment 3 demonstrates reliable, though occasional, violations of an assumption of monotonicity. The observed violations of common assumptions to many models of similarity can be accomodated in terms of dynamic property weighting processes based on specific forms of diagnosticity, and contrast sets that are generated when a comparison is presented.
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  131. Goldstone, R. L., Schyns, P. G., & Medin, D. L. (1997). Learning to bridge between perception and cogntion.  in R. L. Goldstone, P. G. Schyns, & D. L. Medin (Eds.)  Psychology of Learning and Motivation: Perceptual Learning, Vol. 36.  (pp. 1-14).  San Diego, CA: Academic Press.
    Perception
    In building models of cognition, it is customary to commence construction on the foundations laid by perception. Perception is presumed to provide us with an initial source of information that is operated upon by subsequent cognitive processes. And, as with the foundation of a house, a premium is placed on stability and solidity. Stable edifices require stable support structures. By this view, our cognitive processes are well behaved to the degree that they can depend upon the stable structures established by our perceptual system.

    Considered collectively, the contributions to this volume suggest an alternative metaphor for understanding the relation between perception and cognition. The architectural equivalent of perception may be a bridge rather than a foundation. The purpose of a bridge is to provide support, but they do so by adapting to the supported vehicles. Bridges, by design, sway under the weight of heavy vehicles, built on the principle that it is better to bend than break. Bridges built with rigid materials are often less resilient than their more flexible counterparts. Similarly, the chapters collected here raise the possibility that perception supports cognition by flexibly adapting to the requirements imposed by cognitive tasks. Perception may not be stable, but its departures from stability may facilitate rather than hamper its ability to support cognition. Cognitive processes involved in categorization, comparison, object recognition, and language may shift perception, but perception becomes better tuned to these tasks as a result.
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  132. Spencer-Smith, J., & Goldstone, R. L. (1997).  The dynamics of similarity.  Bulletin of the Japanese Cognitive Science Society, 4, 38-56.
    (Translated into Japanese as
    : Spencer-Smith, J., & Goldstone, R. L. (2001).  The dynamics of similarity.  in A. Ohnishi and H. Suzuki (Eds.) Ruii kara mita kokoro (Similarity-based approach to mind).  Tokyo, Japan: Kyoritsu Shuppan.)
    Similarity
    Similarity depends on representations of stimuli that are constructed and changed during comparison-making. Specific features may be selectively weighted during comparison, and the features used in a comparison may themselves be a product of the comparison process. Traditional models of similarity and analogy rely on representations that are assumed to exist prior to comparison and are inflexible. Evidence from previous research indicates that weighting of features in similarity judgments may vary dynamically during processing (Goldstone, 1994; Goldstone & Medin, 1994). SIAM (Goldstone, 1994), a model providing an account of dynamic weighting, is discussed. Additional studies indicate that features may be developed or introduced during similarity judgments. A methodology for examining process-oriented models that may account for flexible representations is proposed.
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  133. Goldstone, R. L. (1996). Isolated and Interrelated Concepts. Memory & Cognition, 24, 608-628
    Concepts Complex
    A continuum between purely isolated and purely interrelated concepts is described. A concept is interrelated to the extent that it is influenced by other concepts. Methods for manipulating and identiying a concept`s degree of interrelatedness are introduced. Relatively isolated concepts are empirically identified by a relatively large use of nondiagnostic features, and by better categorization performance for a concept`s prototype than for a caricature of the concept. Relatively interrelated concepts are identified by minimal use of nondiagnostic features, and by better categorization performance for a caricature than a prototype. A concept is likely to be relatively isolated when: subjects are instructed to create images for their concepts rather than find discriminating features, concepts are given unrelated labels, and the categories that are displayed alternate rarely between trials. The entire set of manipulations and measurements supports a graded distinction between isolated and interrelated concepts. The distinction is applied to current models of category learning, and a connectionist framework for interpreting the empirical results is presented.
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  134. Goldstone, R. L. (1996). Alignment-based nonmonotonicities in similarity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 988-1001.
    Similarity
    According to the assumption of monotonicity in similarity judgments, adding a shared feature in common to two items should increase or leave unchanged, but should never decrease, their similarity. Violations of monotonicity are not predicted by feature- or dimension-based models, but can be accommodated by alignment-based models. According to alignment-based models, when structured displays are compared, the parts of one compared display must be aligned, or placed in correspondence with the parts of the other display. In two experiments, evidence for nonmonotonicities is obtained that is generally, although not entirely, consistent with the alignment-based model SIAM (Similarity as Interactive Activation and Mapping; Goldstone, 1994). The primary assumption of the model is that the calculation of similarity involves an interactive activation process whereby correspondences between the parts of compared displays mutually and concurrently influence each other. As SIAM predicts, the occurrence of nonmonotonicities depends on the perceptual similarity of features and the duration of presented comparisons.
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  135. Goldstone, R. L., Steyvers, M., Larimer, K. (1996). Categorical perception of novel dimensions. Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society. (pp 243-248). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Concepts Perception
    Categorical perception is a phenomenon in which people are better able to distinguish between stimuli along a physical continuum when the stimuli come from different categories than when they come from the same category. In a laboratory experiment with human subjects, we find evidence for categorical perception along a novel dimension that is created by interpolating (i.e. morphing) between two randomly selected bezier curves. A neural network qualitatively models the empirical results with the following assumptions: 1) hidden ÒdetectorÓ unit become specialized for particular stimulus regions with a topologically structured competitive learning algorithm, 2) simultaneously, associations between detectors and category units are learned, and 3) feedback from the category units to the detectors causes the detectors to become concentrated near category boundaries. The particular feedback used, implemented in an "S.O.S. network," operates by increasing the learning rate to detectors that are neighbors to a detector that produces an improper categorization.
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  136. Kroska, A., & Goldstone, R. L. (1996). Dissociations in the similarity and categorisation of emotions. Cognition and Emotion,10, 27-45.
    Similarity

    Most studies of the categorization of emotions tests the prototype model against the classical model, concluding that the prototype model offers the better explanation. Prototype models, as with all similarity-based models, posit that categorization depends on the similarity between the instance to be categorized and the category representation. However, we find that emotion similarity judgments and categorization judgments sometimes diverge. Specifically, information about changes in a person`s status and/or potency is weighted more heavily in categorization decisions than it is in similarity decisions. We argue that a knowledge-based model, rather than a similarity-based model, offers the best account of emotion categorization when information about status and potency changes is avail.able.
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  137. Levine, G. M., Halberstadt, J. B., & Goldstone, R. L. (1996). Reasoning and the weighting of attributes in attitude judgments. Journal of Personality and Social Psychology, 70, 230-240.
    Perception
    The experiments examined processes by which analyzing reasons may influence attitude judgments. Participants made multiple liking judgments on sets of stimuli that varied along six a priori dimensions. In Study 1, the stimulus set consisted of 64 cartoon faces with six binary-valued attributes (e.g. a straight versus crooked nose). In Study 2, the stimuli were 60 digitized photographs from a college yearbook that varied along six dimensions uncovered through multi-dimensional scaling. In each experiment, half of the participants were instructed to think about the reasons why they liked each face before making their liking rating. Participants` multiple liking ratings were then regressed on the dimension values to determine how they weighted each dimension in their liking judgments. Results support a process whereby reasoning leads to increased variability and inconsistency in the weighting of stimulus information. Results are discussed with respect to Wilson`s model of the disruptive effects of reasoning on attitude judgments (e.g. Wilson, Dunn, Kraft, & Lisle, 1989).
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  138. Goldstone, R. L. (1995). Effects of categorization on color perception. Psychological Science, 6, 298-30
    Concepts Perception
    Subjects were shown simple objects and were asked to reproduce the colors of the objects. Even though the objects remained on the screen while the subjects reproduced the colors and the objects` shapes were irrelevant to the subjects` task, subjects` color perceptions were influenced by the shape category of an object. For example, objects that belonged to categories with redder objects were judged to be more red than identically colored objects belonging to another category. Further experiments showed thatX the object categories that subjects use, rather than being fixed, depend on the objects to which subjects are exposed.
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  139. Goldstone, R. L. (1995). Mainstream and avant-garde similarity. Psychologica Belgica, 35, 145-165.
    Similarity
    In the first part of this article, empirical evidence is reviewed that suggests a substantial amount of flexibility and context-sensitivity in peopleUs judgments of similarity. Four examples of flexible similarity from our laboratory are considered in detail. In the second part of the article, evidence for relatively constrained, invariant similarity assessments is considered. In the final section, a resolution to these apparently contradictory views on similarity is proposed. Assessments of similarity are used to make inferences from one entity to another. In some situations, flexible similarity is needed to tailor inferences to oneUs knowledge of the entities and their relations. In other situations, particularly those in which specific knowledge is missing or unavailable, a relatively constant similarity is needed to establish generally permissible inferences. Thus, the flexibility and stability of similarity may reflect its different cognitive uses.
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  140. Medin, D. L., & Goldstone, R. L. (1995). The predicates of similarity. In C. Cacciari (Ed.), Similarity in Language, Thought, and Perception. (pp. 83-110). Brussels: BREPOL.
    Similarity


  141. Medin, D. L., Goldstone, R. L., & Markman, A. (1995). Comparison and choice: Relations between similarity processes and decision processes. Psychonomics Bulletin and Review, 2, 1-19.
    Similarity
    Research and theory in decision making and in similarity judgment have developed along parallel paths. We review and analyze phenomena in both domains that suggest that similarity processing and decision making share important correspondences. The parallels are explored at the level of empirical generalizations and underlying processing principles. Important component processes that are shared by similarity judgments and decision making include generation of alternatives, recruitment of reference points, dynamic weighting of aspects, creation of new descriptors, development of correspondences between items, and justification of judgement.
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  142. Goldstone, R. L. (1995). Many categories, few structures. Contemporary Psychology, 40, 147-149.
    Concepts

  143. Goldstone, R. L. (1994). Influences of categorization on perceptual discrimination. Journal of Experimental Psychology: General, 123, 178-200.
    Similarity Concepts Perception
    Four experiments investigated the influence of categorization training on perceptual discriminations. Ss were trained according to 1 of 4 different categorization regimes. Subsequent to category learning, Ss performed a Same-Different judgement task. Ss` sensitivities (d`s) for discriminating between items that varied on a category(ir)relevant dimensions were measured. Evidence for acquired distinctiveness (increased perceptual sensitivity for items that are categorized differently) was obtained. One case of acquired equivalence (decreased perceptual sensitivity for items that are categorized together) was found for separable, but not integral, dimensions. Acquired equivalence within a categorization-relevant dimension was never found for either integral or separable dimensions. The relevance of the results for theories of perceptual learning, dimensional attention, categorical perception, and categorization are discussed.
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  144. Goldstone, R. L. (1994). The role of similarity in categorization: Providing a groundwork. Cognition, 52, 125-157.
    Similarity Perception

    The relation between similarity and categorization has recently come under scrutiny from several sectors. The issue provides an important inroad to questions about the contributions of high-level thought and lower-level perception in the development of people`s concepts. Many psychological models base categorization on similarity, assuming that thing belong in the same category because of their similarity. Empirical and in-principle arguments have recently raied objections to this connection, on the grounds that similarity is too unconstrained to provide an explanation of categorization, and similarity is not sufficiently sophisticated to ground most categories. Although these objections have merit, a reassesment of evidence indicates that similarity can be sufficiently constrained and sophisticated to provide at least a partial account of many categories. Principles are discussed for incorporating similarity into theories of category formation.
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  145. Goldstone, R. L. (1994). Similarity, Interactive Activation, and Mapping. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 3- 28.
    Similarity Complex
    The question of "what makes things seem similar?" is important both for the pivotal role of similarity in theories of cognition and for an intrinsic interest in how people make comparisons. Similarity frequently involves more than listing the features of the things to be compared and comparing the lists for overlap. Often, the parts of one thing must be aligned or placed in correspondence with the parts of the other. The quantitative model with the best overall fit to human data assumes an interactive activation process whereby correspondences between the parts of compared things mutually and concurrently influence each other. An essential aspect of this model is that matching and mismatching features influence similarity more if they belong to parts that are placed in correspondence. In turn, parts are placed in correspondence if they have many features in common and if they are consistent with other developing correspondences.
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  146. Goldstone, R. L. (1994). An efficient method for obtaining similarity data. Behavior Research Methods, Instruments, & Computers, 26, 381-386.
    Similarity
    Measurements of similarity have typically been obtained through the use of rating, sorting, and perceptual confusion tasks. In the present paper, a new method of measuring similarity is described, in which subjects rearrange items so that their proximity on a computer screen is proportional to their similarity. This method provides very efficient data collection. If a display has n objects, then, after subjects have rearranged the objects (requiring slightly more than n movements), n(n-1)/2 pairwise similarityes can be recorded. As long as the constraints imposed by two-diminsional space are not too different from those intrinsic to psychological similarity, the technique apears to offer an efficient, user-friendly, and intuitive process for measuring psychological similarity.
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  147. Goldstone, R. L. (1994). Categorization. Science, 265, 552. [review of Estes` Classification and Cognition]
    Concepts

  148. Goldstone, R. L., & Kruschke, J. K. (1994). Are rules and instances subserved by separate systems? [A commentary on Shanks and St. John]. Behavioral and Brain Sciences, 17, 405.
    Concepts

  149. Goldstone, R. L., & Medin, D. L. (1994). The time course of comparison. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 29-50.
    Similarity
    Similarity as interactive activation and mapping (SIAM), a model of the dynamic course of similarity comparisons, is presented. According to SIAM, when structured scenes are compared, the parts of one scene must be aligned, or placed in correspondence, with the parts from the other scene. Emerging correspondences influence each other in a manner such that, with sufficient time, the strongest correspondences are those that are globally consistent with other correspondences. Relative to globally inconsistent feature matches, globally consistent feature matches influence similarity more when greater amounts of time are given for a comparison. A common underlying process model of scene alignment accounts for commonalities between different task conditions. Differences between task conditions are accounted for by principled parametric variation within the model.
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  150. Goldstone, R.L., & Medin, D.L. (1994). Interactive activation, similarity, and mapping: An overview. in K. Holyoak and J. Barnden (Eds.) Advances in Connectionist and Neural Computation Theory, Vol. 2: Analogical Connections. (pp. 321-362). Ablex : New Jersey.
    Similarity

    The organization of this chapter is as follows. First, we review the role of mapping and global consistency in both low-level visual perception and abstract analogy and then suggest that mapping and consistency also apply to similarity assessment. Next, we review current models of similarity and note that they have little to say about processes by which corresponding properties are aligned. We then describe some experiments on alignment processes associated with comparisons. We account for these results with an interactive activation model of alignment and contrast this model with a number of alternative.s Finally, we asses the role of mapping or alignment in comparisons more generally and offer some conclusions.
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  151. Goldstone, R. L., & Schyns, P. (1994). Learning new features of representation. Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. (pp. 974-978). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Perception
    One productive and influential approach to cognition maintains that categorization, object recognition, and higher-level cognitive processes operate on the output of lower-level perceptual processing.That is, our perceptual systems provide us with a set of fixed features. These features are the inputs to higher-level cognitive processes.

     Recently, researchers in psychology, computer science, and philosophy have questioned this unidirectional approach, arguing that in many situations, the high-level cognitive process being executed has an influence on the lower-level features that are created. For example, in addition to categorization being based on featural descriptions of objects, it might also be the case that the categorization process partially creates the featural decriptions that are used. Rather than viewing the "vocabulary" of primitives to be fixed by low-level processes, this view maintains that the vocabulary is dependent on the higher-level process that uses the vocabulary. This symposium will investigate several issues related to bidirectional interactions between high-level and low-level cognitive processes.
  152. McGraw, G., Rehling, J., & Goldstone, R. L. (1994). Letter perception: Toward a conceptual approach. Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. (pp. 613-618). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Perception
    We present the results of a simple experiment in lower-case letter recognition. Unlike most psychology studies of letter recognition, we include in our data set letters at the extremes of their categories and investigate the recognition of letters of multiple typefaces. We are interested in the relationship between the recognition of normal letters and the recognition of non-standard letters. Results provide empirical evidence for top-down conceptual constrains on letter perception in the form of roles and relations between perceptually-based stuctural subcomponents. A process model based on the hypothesis developed below is currently being implemented.
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  153. Pevtzow, R., & Goldstone, R. L. (1994). Categorization and the parsing of objects. Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. (pp. 717-722). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Concepts Perception
    Several models of categorization suggest that fixed inputs (features) are combined together to create categorization rules. It is also possible that categorization influences what features are perceived and used. This experiment explored the possibility that categorization training influences how an object is decomposed into parts. In the first part of this experiment, subjects learned to categorize objects based on particular sets of line segments. Following categorization training, subjects were tested in a whole-part decomposition task, making speeded judgements of "does whole X contain probe Y." All diagnostic and nondiagnostic category parts were used as parts within the whole objects, and as probes. Categorization training in the first part of the experiment affected performance on the second task. In particular, subjects were faster to respond when the whole object contained a part that was diagnostic for categorization than when it contained a nondiagnostic part. When the probe was a diagnostic category part subjects were faster to respond that it was present than absent, and when the probe was a nondiagnostic part, subjects were faster to respond that it was absent than that it was present. These results are discussed in terms of perceptual sensitivity, response bias, and the modulating influence of experience.
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  154. Goldstone, R. L. (1993). Feature distribution and biased estimation of visual displays. Journal of Experimental Psychology: Human Perception and Performance, 19, 564-579.
    Perception
    Perceptual equivalents of confirmation biases and framing effects are observed in subjects` estimates of feature numerosity. Subjects are asked to estimate the percentage of display items that have a particular feature. Features either are randomly distributed or are spatially clustered such that features of the same type tend to be close. Subjects systematically overestimate the prevalence of features in clustered displays. The pattern of results is best explained by a reional salience bias: Features tend to be more salient if they belong to regions that have a high concentration of instruction-mentioned features. The regional salience bias is contrasted with a feature salience bias: Features tend to be more salient if they are mentioned in the instructions. The relations among the observed perceptual bias and traditional confirmation biases, numeric estimation, and attention are discussed.
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  155. Goldstone, R. L. (1993). Evidence for interrelated and isolated concepts from prototype and caricature classifications. Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society. (pp. 498-503). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Concepts

    Previous research (Goldstone, 1991) has suggested that concepts differ in their degree of dependency on other concepts. While some concepts` characterizations depend on other simultaneously acquired concepts, other concepts are relatively isolated. The current experiments provide a new measure of a concept`s interrelatedness/isolation. It is assumed that if the prototype of a concept is classified with greater accuracy than a caricature, then the concept is relatively independent of the influences of other concepts. If a caricature is more easily categorized than the prototype, then the concept is relatively dependent on other concepts. If these assumptions are made, then the current experiments provide converging support for a interrelated/isolated distinction. Instructing subjects to form images of the concepts to be acquired, or infrequently alternating categories during presentation, yields relatively isolated concepts. Instructing subjects to try to discriminate between concepts, or frequently alternative categories, yields relatively interrelated concepts.

  156. Goldstone, R. L., & Chin, C. (1993). Dishonesty in self-report of copies made: Moral relativity and the Xerox machine. Basic and Applied Social Psychology, 14, 19-32.

    This study involved noninvasive observation of copy-machine use at a university institution. Patrons` self-reports of copies were compared to the actual number of copies made. Results indicate a systematic underreporting of actual copies. Intermediate-level dishonesty is common place, whereby patrons underestimate the number of copies made but refrain from profit-maximizing dishonesty even in the absence of an external monitor. The percentage of copies unreported is approximately constant over different copy job sizes. There are strong self-imposed constraints on the level of allowed dishonesty. However, there is an increased tendency for intermediate-level dishonesty as copy job size increases. Nonreporting of copies and correct reporting of copies are both common for small jobs. There is an empirical dissociation between the prevalence and the degree of dishonest behaviors, interpretable in terms of different motivations that arise when financial gains are high and low. The results are also diagnostic in assessing the nature of the tradeoff between the competing motivations to maximize financial profits and to behave honestly.

  157. Goldstone, R. L. (1993). Human Cognition, and the More General Case. Contemporary Psychology, 38, 61-62.

  158. Medin, D.L., Goldstone, R.L., & Gentner, D. (1993). Respects for similarity. Psychological Review, 100, 254-278.
    Similarity
    This article reviews the status of similarity as an explanatory construct with a focus on similarity judgements. For similarity to be a useful construct, one must be able to specify the ways or respects in which two things are similar. One solution to this problem is to restruct the notion of similarity to hard-wired perceptual processes. It is argued that this view is too narrow and limiting. Instead, it is proposed that an important source of constraints derives from the similarity comparison process itself. Both new experiments and other evidence are described that support the idea that respects are determined by processes internal to comparisons.
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  159. Goldstone, R. L. (1992). Locally-to-globally consistent processing in similarity. Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society. (pp. 337-342). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
  160. Aha, D. W., and Goldstone, R. L. (1992). Concept learning and flexible weighting. Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society. (pp. 534-539). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Concepts
    We previously introduced an exemplar model, named GCM-ISW, that exploits a highly flexible weighting scheme. Or simulations showed that it records faster learning rates and higher asymptotic accuracies on several artificial categorization tasks than models with more limited abilities to warp input spaces. This paper extends our previous work; it describes experimental results that suggest human subjects also invoke such highly flexible schemes. In particular, our model provides significantly better fits than models with less flexibility, and we hypothesize that humans selectively weight attributes depending on an item`s location in the input space.

  161. Goldstone, R. L. (1991). Feature diagnosticity as a tool for investigating positively and negatively defined concepts. Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society. (pp. 263-268). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Concepts
    Two methods of representing concepts are distinguished and empirically investigated. Negatively defined concepts are defined in terms of other concepts at the same level of abstraction. Positively defined concepts do not make recourse to other concepts at the same level of abstraction for their definition. In two experiments, subjects are biased to represent concepts underlying visual patterns in a positive manner by instructing subjects to form an image of the learned concepts and by initially training subjects on minimally distorted concept instances. Positively defined concepts are characterized by a large use of nondiagnostic features in concept representations, relative to negatively defined concepts. The distinction between positively and negatively defined concepts can account for the dual nature of natural concepts - as directly accessed during the recognition of items, and is intricately interconnected to other concepts.

  162. Goldstone, R. L., Medin, D. L., & Gentner, D. (1991). Relational similarity and the nonindependence of features in similarity judgments. Cognitive Psychology, 23, 222-264
    Similarity
    Four experiments examined the hypothesis that simple attributional features and relational features operate differently in the determination of similarity judgements. Forced choice similarity judgments ("Is X or Y more similar to Z?") and similarity rating tasks demonstrate that making the same featural change in two geometric stimuli unequally affects their judged similarity to a third stimulus (the comparison stimulus). More specifically, a featural change that causes stimuli to be more superficially similar and less relationally similar increases judged similarity if it occurs in stimuli that already share many superficial attributes, and decreases similarity if it occurs in stimuli that do not share as many superficial attributes. These results argue against an assumption of feature independence which asserts that the degree to which a feature shared by two objects affects similarity is independent of the other features shared by the objects. The MAX hypothesis is introduced, in which attributional and relational similarities are separately pooled, and shared features affect similarity more if the pool they are in is already relatively large. The results support claims that relations and attributes are psychologically distinct and that formal measures of similarity should not treat all types of matching features equally.
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  163. Medin, D. L., Goldstone, R. L. (1991). Concepts. In B. Blackwell (Ed.) Dictionary of Cognitive Psychology (pp 77-83). Oxford: Oxford University Press.
    Concepts
  164. Aha, D. W., and Goldstone, R. L. (1990). Learning attribute relevance in context in instance-based learning algorithms. Proceedings of the Twelfth Annual Conference of the Cognitive Science Society. (pp. 141-148). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Concepts
    There has been an upsurge of interest, in both artificial intelligence and cognitive psychology, in exemplar-based process models of categorization, which preserve specific instances instead of maintaining abstractions derived from them. Recent exemplar-based models provided accurate fits for subject results in a variety of experiments because, in accordance with Shepard`s (1987) observations, they define similarity to degrade exponentially with the distance between instances in psychological space. Although several researchers have shown that an attribute`s relevance in similarity calculations varies according to its context (i.e., the values of the other attributes in the instance and the target concept," previous exemplar models define attribute relevance to be invariant across all instances. This paper introduces the GCM-ISW model, an extension of Nosofsky`s GCM model that uses context-specific attribute weights for categorization tasks. Since several researchers have reported that humans make context-sensitive classification decision, our model will fit subject data more accurately when attribute relevance is context-sensitive. We also introduce a process component for GCM-ISW and show that its learning rate is significantly faster than the rates of both previous exemplar-based process models when attribute relevance varies among instances. GCM-ISM is both computationally more efficient and more psychologically plausible than previous exemplar-based models.

  165. Medin, D. L., Ahn, W-K, Bettger J., Florian, F., Goldstone, R., Lassaline, M., Markman, A., Rubinstein, J., Wisniewski, E. (1990). Safe Takeoffs-Soft Landings. Cognitive Science, 14, 169-178.
    Concepts

  166. Medin, D. L., Goldstone, R. L., & Gentner, D. (1990). Similarity involving attributes and relations: Judgments of similarity and difference are not inverses. Psychological Science, 1, 64-69.
    Similarity
    Conventional wisdom and previous research suggest that similarity judgements and difference judgements are inverses of one another. An exception to this rule arises when both relational similarity and attributional similarity are considered. When presented with choices that are relationally or attributionally similar to a standard, human subjects tend to pick the relationally similar choice as more similar to the standard and as more different from the standard. These results not only reinforce the general distinction between attributes and relations but also show that attributes and relations are dynamically distinct in the processes that give rise to similarity and difference judgments.
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  167. Goldstone, R. L., Gentner, D., & Medin, D. L. (1989). Relations Relating Relations. Proceedings of the Eleventh Annual Conference of the Cognitive Science Society. (pp. 131-138). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
    Similarity

  168.   Matheus, C. J., Rendall, L. R., Medin, D. L., & Goldstone, R. L. (1989). Purpose and conceptual functions: A framework for concept representation and learning in humans and machines. The Seventh Conference of the Society for the Study of Artificial Intelligence and Simulation of Behavior. Sussex, England.
     Concepts