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A simulation model of episodic memory, MINERVA 2, is applied to the learning of concepts, as represented by the scbema-abstraction task. The model assumes that each experience produces a separate memory trace and that knowledge of abstract concepts is derived from the pool of episodic traces at the time of retrieval. A retrieval cue contacts all traces simultaneously, activating each according to its similarity to the cue, and the information retrieved from memory reflects the summed content of all activated traces responding in parallel. The MINERVA 2 model is able to retrieve an abstracted prototype of the category when cued with the category name and to retrieve and disambiguate a category name when cued with a category exemplar. The model successfully predicts basic findings from the schema-abstraction literature (e.g., differential forgetting of prototypes and old instances, typicality, and category size effects), including some that have been cited as evidence against exemplar theories of concepts. The model is compared to other classification models, and its implications regarding the abstraction problem are discussed. How is abstract knowledge related to specific experience? In present-day terms, this question concerns the relationship between episodic and generic memories. This article explores the possibility that there is only one memory system, which stores episodic traces, and that abstract knowledge as such does not have to be stored but can be derived from the pool of traces of specific experiences at the time of retrieval. I demonstrate how this might work by applying a simulation model of a multipletrace memory theory to the schema-abstraction experimental paradigm, which is widely believed to capture in the laboratory the processes by which generic or abstract ideas are formed. Multiple-trace theories assume that each event to which one attends gives rise to its own memory trace. Thus, repetition of an item such as a word in a list does not strengthen a prior representation (Le., one predating the experiment or one laid down by the item's first experimental occurrence); rather, it produces a new trace that coexists in memory with traces of other occurrences of the same item. Experiments supporting the multiple-trace assumption have been primarily concerned with the ability of subjects to remember an item's presentation frequency, list membership, presentation modality, exposure duration, serial position, and so forth (e.g., Thanks are due to the MRC Applied Psychology Unit, Cambridge, England, for the use of their facilities in some of this work. Correspondence concerning this article should be addressed to Douglas L. Hintzman, Department of Psychology, University of Oregon, Eugene, Oregon 97403. 411 trace theories are primarily accounts of how repetition affects episodic memory. We become familiar with concepts, however, through repeated encounters with category members, and so repetition also plays a role in the acquisition of abstract categories. Is this effect of repetition mediated by a different mechanism than the one involved in episodic memory tasks? One view is that it is, and that repeated exposure to exemplars of a category produces not only traces of the individual events in an episodic memory system but also a unitary, abstract representation of the category in a functionally separate generic memory system (e.g., Tulving, 1983). The alternative view under consideration here is that only traces of the individual episodes are stored and that aggregates of traces acting in concert at the time of retrieval represent the category as a whole. The simulation model shows, in principle, how the latter might be accomplished. It demonstrates, moreovet; that a multiple-trace model comprising a simple set of episodic memory assumptions can account for many of the phenomena that have been reported in the literature on the schema-abstraction task. There appear to be two basic ways in which people learn to classify objects and events. One is through the presentation and naming of category exemplars (as a child typically learns to tell dogs from cats). The other is through explicit communication about definitions (e.g., that of prime number), exceptions (e.g., a bat is not a bird), and the like. Learning through examples appears to be a prerequisite to learning through communication, in that the latter depends on the learner's knowing the meanings of at least some of the words. One reason for concentrating on the schema-abstraction task, rather than naturally learned concepts, is that the task appears to capture in the laboratory the more basic of these two types of learning, unconfounded by the acquisition of information through language. A second reason is that the task allows careful control of variables crucial to the understanding oflearning-such as the frequency, recency, and similarity of exemplars-which are usually unknown in the case of naturally learned concepts. For these rea

Why are Formal Models Useful in Psychology?

18 pagesThis chapter explores the value of formal (mathematical and computer) models in psychology. Research on factors that have been shown to bias and limit unaided human reasoning is briefly reviewed, and it is noted that psychologists are susceptible to these errors, just as their subjects are. Characteristics of formal models are discussed in relation to such errors, in an effort to identify the ways in which models can and cannot aid scientific thought. Some limitations of the modeling approach are also discussed. It is argued that because psychological models greatly oversimplify the domains to which they are applied, model evaluation is a complex matter. The measure of a model's value lies not in its ability to fit data, but in how much we can learn from it.This research was supported by grant BNS-87-11218, from the National Science Foundation

The Psychology of learning and memaory

xvi, 456 p.; 24 cm