Differential forgetting of prototypes and old instances: Simulation by an exemplar-based classification model
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- Volume 8, pages 378β382 (1980)
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Abstract
A common finding in studies of classification learning is that ability to classify the prototype of a category declines much less over a retention interval than does the ability to classify the previously seen exemplars themselves. We demonstrate here that this finding does not necessarily indicate the existence, in memory, of a representation of the prototype. MINERVA, a computer-simulation model that encodes memory traces only of presented exemplars, was tested on an appropriate task. Differential forgetting of prototypes and old instances was shown by a version of the model that assumed that (1) classification is based on the exemplar trace most similar to the test stimulus and (2) individual properties are lost from the traces over time in an all-or-none fashion. It is suggested that, in general, the key to the prediction of differential forgetting may be the concomitance of forgetting and generalization.
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Bahrick, H. P., Clark, S., &Bahrick, P. Generalization gradients as indicants of learning and retention of a recognition task.Journal of Experimental Psychology, 1967,75, 464β471.
Bower, G. H. A multicomponent theory of the memory trace. In K. W. Spence & J. T. Spence (Eds.),The psychology of learning and motivation (Vol. 10). New York: Academic Press, 1967.
Brooks, L. Nonanalytic concept formation and memory for instances. In E. Rosch & B. B. Lloyd (Eds.),Cognition and categorization. Hillsdale, N.J: Erlbaum, 1978.
Gibson, E. J. A systematic application of the concepts of generalization and differentiation to verbal learning.Psychological Review, 1940,47, 196β229.
Hintzman, D. L.The psychology of learning and memory. San Francisco: Freeman, 1978.
Homa, D., Cross, J., Cornell, D., Goldman, D., &Schwartz, S. Prototype abstraction and classification of new instances as a function of number of instances defining the prototype.Journal of Experimental Psychology, 1973,101, 116β122.
Medin, D. L., &Schaffer, M. M. Context theory of classification learning.Psychological Review, 1978,85, 207β238.
Posner, M. I., &Keele, S. W. Retention of abstract ideas.Journal of Experimental Psychology, 1970,83, 304β308.
Reed, S. K. Pattern recognition and categorization.Cognitive Psychology, 1972,3, 382β407.
Robbins, D., Barresi, J., Compton, P., Furst, A., Russo, M., &Smith, M. A. The genesis and use of exemplar vs. prototype knowledge in abstract category learning.Memory & Cognition, 1978,6, 473β480.
Schacter, D. L., Eich, J. E., &Tulving, E. Richard Semonβs theory of memory.Journal of Verbal Learning and Verbal Behavior, 1978,17, 721β743.
Semon, R. [Mnemic psychology] (B. Duffy, trans.). London: George Allan & Unwin, 1923.
Strange, W., Kenney, T., Kessel, F., &Jenkins, J. Abstraction over time of prototypes from distortions of random dot patterns.Journal of Experimental Psychology, 1970,83, 508β510.
Tversky, A. Features of similarity.Psychological Review, 1977,84, 327β352.
Underwood, B. J. An evaluation of the Gibson theory of verbal learning. In C. N. Cofer (Ed.),Verbal learning and verbal behavior. New York: McGraw-Hill, 1961.
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This material is based upon work supported by the National Science Foundation under Grant BNS-7824987.
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Hintzman, D.L., Ludlam, G. Differential forgetting of prototypes and old instances: Simulation by an exemplar-based classification model. Memory & Cognition 8, 378β382 (1980). https://doi.org/10.3758/BF03198278
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DOI: https://doi.org/10.3758/BF03198278
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