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Presolution Performance Functions for Markov Models

Published online by Cambridge University Press:  01 January 2025

Peter G. Polson
Peter G. Polson*
Affiliation:
University of Colorado
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Abstract

Performance measures, conditionalized on the last error and other events, have been of central concern in the development of absorbing Markov-chain models for learning and problem solving. Expressions for response probabilities and expected latencies conditional on the occurrence of the last error and other events are derived using matrix methods.

Information

Type
Original Paper
Information
Psychometrika , Volume 37 , Issue 4 , December 1972 , pp. 453 - 459
Copyright
Copyright © 1972 The Psychometric Society

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References

Bernbach, H. A. Derivation of learning process statistics for a general Markov model. Psychometrika, 1966, 31, 225–23410.1007/BF02289509CrossRefGoogle ScholarPubMed
Bower, G. H. Application of a model to paired-associates learning. Psychometrika, 1961, 26, 255–28010.1007/BF02289796CrossRefGoogle Scholar
Bower, G. H. An association model for response and training variables in paired-associate learning. Psychological Review, 1962, 69, 34–5310.1037/h0039023CrossRefGoogle ScholarPubMed
Bower, G. H. Notes on a descriptive theory of memory. In Kimble, D. P. (Eds.), Learning, remembering, and forgetting: Proceedings of the Second Conference, 1967, New York: New York Academy of ScienceGoogle Scholar
Kemeny, J. G., & Snell, J. L. Finite Markov Chains, 1960, Princeton: Van NostrandGoogle Scholar
Millward, R. Latency in a modified paired-associate learning experiment. Journal of Verbal Learning and Verbal Behavior, 1964, 3, 309–316CrossRefGoogle Scholar
Millward, R. B. Derivations of learning statistics from absorbing Markov chains. Psychometrika, 1969, 34, 215–232CrossRefGoogle Scholar
Polson, P. G., & Greeno, J. G. Nonstationary performance before all-or-none learning. Psychological Review, 1969, 76, 227–231CrossRefGoogle Scholar
Suppes, P., & Ginsberg, R. A fundamental property of all or none models, binomial distribution of responses prior to conditioning, with application to concept formation in children. Psychological Review, 1963, 70, 139–161CrossRefGoogle ScholarPubMed
Suppes, P., Groen, G., & Schlag-Rey, M. A model for response latency in paired-associate learning. Journal of Mathematical Psychology, 1966, 3, 99–128CrossRefGoogle Scholar
Trabasso, T., & Bower, G. Component learning in the four-category concept problem. Journal of Mathematical Psychology, 1964, 1, 143–169CrossRefGoogle Scholar