Evaluating case-based decision theory: Predicting empirical patterns of human classification learning

Andreas Pape and Kenneth J. Kurtz

Games and Economic Behavior, 2013, vol. 82, issue C, 52-65

Abstract: We introduce a computer program which calculates an agentʼs optimal behavior according to case-based decision theory (Gilboa and Schmeidler, 1995) and use it to test CBDT against a benchmark set of problems from the psychological literature on human classification learning (Shepard et al., 1961). This allows us to evaluate the efficacy of CBDT as an account of human decision-making on this set of problems.

Keywords: Case-based decision theory; Human cognition; Learning; Agent-based computational economics; Psychology; Cognitive science (search for similar items in EconPapers)
JEL-codes: C63 C88 D83 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:gamebe:v:82:y:2013:i:c:p:52-65

DOI: 10.1016/j.geb.2013.06.010

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