Beyond exemplars and prototypes as memory representations of natural concepts: A clustering approach (original) (raw)
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Episodic and prototype models of category learning
Cognitive Processing
The question of what processes are involved in the acquisition and representation of categories remains unresolved despite several decades of research. Studies using the well-known prototype distortion task (Posner and Keele in J Exp Psychol 77:353-363, 1968) delineate three candidate models. According to exemplar-based models, we memorize each instance of a category and when asked to decide whether novel items are category members or not, the decision is explicitly based on a similarity comparison with each stored instance. By contrast, prototype models assume that categorization is based on the similarity of the target item to an implicit abstraction of the central tendency or average of previously encountered instances. A third model suggests that the categorization of prototype distortions does not depend on pre-exposure to study exemplars at all and instead reflects properties of the stimuli that are easily learned during the test. The four experiments reported here found evidence that categorization in this task is predicated on the first and third of these models, namely transfer at test and the exemplarbased model. But we found no evidence for the second candidate model that assumed that categorization is based on implicit prototype abstraction.
Development of Prototype Abstraction and Exemplar Memorization
2010
Development of Prototype Abstraction and Exemplar Memorization Irina Baetu (irina.baetu@mail.mcgill.ca) Department of Psychology, McGill University, 1205 Penfield Avenue Montreal, QC H3A 1B1 Canada Thomas R. Shultz (thomas.shultz@mcgill.ca) Department of Psychology and School of Computer Science, McGill University, 1205 Penfield Avenue Montreal, QC H3A 1B1 Canada likely to rely on prototypes at the beginning of a categorization task, and as training progresses they rely more on memorized exemplars (Horst, Oakes, & Madole, 2005; Minda & Smith, 2001; Smith & Minda, 1998). These studies are consistent with a shift from early prototype use to later exemplar memorization. In addition to the amount of experience with a categorization task, category structure also influences which type of information is most used. Better-structured categories can be represented as separate clusters in psychological space, whereas poorly structured categories overlap with each other (Figure 1). Smith and Mi...
The genesis and use of exemplar vs. prototype knowledge in abstract category learning
Memory & Cognition, 1978
Accurate classification of new exemplars in an abstraction paradigm may be due to their similarity to old exemplars rather than to abstract category (or prototype) knowledge. In the present study, subjects received initial training on a two-category problem before being transferred to a task in which half of the exemplar-response pairs had their responses reversed while the remaining half of the pairs were unchanged. When transfer occurred with no delay and involved old exemplars, more errors occurred for changed than for unchanged pairs. This result implies the use of exemplar-specific rather than abstract category knowledge. However, when transfer was delayed by 24 or 72 h, errors occurred equally often for changed and unchanged pairs. This result suggests that exemplar-specific knowledge is no longer used. Since subjects were still able to accurately classify exemplars prior to the transfer task at these delays, some form of abstract category knowledge is implicated.
Cue abstraction and exemplar memory in categorization
Journal of Experimental Psychology: Learning, Memory, and Cognition, 2003
In this article, the authors compare 3 generic models of the cognitive processes in a categorization task. The cue abstraction model implies abstraction in training of explicit cue-criterion relations that are mentally integrated to form a judgment, the lexicographic heuristic uses only the most valid cue, and the exemplar-based model relies on retrieval of exemplars. The results from 2 experiments showed that, in lieu of the lexicographic heuristic, most participants spontaneously integrate cues. In contrast to single-system views, exemplar memory appeared to dominate when the feedback was poor, but when the feedback was rich enough to allow the participants to discern the task structure, it was exploited for abstraction of explicit cue-criterion relations.
Journal of Experimental Psychology: Learning, Memory, and Cognition, 2002
presented evidence that they claimed challenged the predictions of exemplar models and that supported prototype models. In the authors' view, this evidence confounded the issue of the nature of the category representation with the type of response rule (probabilistic vs. deterministic) that was used. Also, their designs did not test whether the prototype models correctly predicted generalization performance. The present work demonstrates that an exemplar model that includes a response-scaling mechanism provides a natural account of all of Smith et al.'s experimental results. Furthermore, the exemplar model predicts classification performance better than the prototype models when novel transfer stimuli are included in the experimental designs.
Categorization of novel stimuli in well-known natural concepts: A case study
Psychonomic Bulletin & Review, 2001
In this study, we investigated to what extent exemplar-based and prototype predictors can be applied to predicting categorization in natural language concepts. Participants categorized novel tropical foods into two well-known natural language concepts: fruits and vegetables. The results indicate that both the prototype predictors and the exemplar predictors contribute significantly in accounting for the categorization choices but that the contribution of the prototype predictor comes from just a limited number of features.
Exemplars, prototypes, and similarity rules
Subjects learned to classify perceptual stimuli varying along continuous, separable dimensions into rule-described categories. The categories were designed to contrast the predictions of a selective-attention exemplar model and a simple rule-based model formalizing an economy-ofdescription view. Converging evidence about categorization strategies was obtained by also collecting identification and recognition data and by manipulating strategies via instructions. In free-strategy conditions, the exemplar model generally provided an accurate quantitative account of identification, categorization, and recognition performance, and it allowed for the interrelationship of these paradigms within a unified framework. Analyses of individual subject data also provided some evidence for the use of rules, but in general, the rules seemed to have a great deal in common with exemplar storage processes. Classification and recognition performance for subjects given explicit instructions to use specific rules contrasted dramatically with performance in the free-strategy conditions and could not be predicted by the exemplar model.