Theory of Adaptive Decision Making

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The purpose of this research is to investigate how individuals learn to improve their decision-making skills on the basis of experience resulting from consequences of past decisions. The research was designed to evaluate empirically a mathematical learning theory that can be summarized by three principles: The first principle describes how each situation is categorized for the purpose of identifying a set of appropriate decision-making rules; the second principle describes how one particular rule is selected from a set of competing rules on the basis of average past performance; and the third principle describes how the performance of each decision rule is slowly improved by a fine tuning process guided by feedback from previous consequences. The first two experiments will test the hypothesis that a simple "hill-climbing" mechanism is used to fine tune and improve the performance of a given rule. Experiment 1 will investigate how diagnostic criteria are learned in a medical diagnosis task, and Experiment 2 will investigate how individuals learn to improve resource allocations to maximize profits. The next two experiments will test the hypothesis that rules are selected on the basis of performance estimates produced by a recency-weighted averaging mechanism. Experiment 3 will investigate how individuals learn to choose among fictitious medical treatments that differ according to efficacy, and Experiment 4 will investigate how individuals learn to choose among diagnostic rules for categorizing fictitious medical patients. The last two experiments will test the hypothesis that decision situations are categorized prior to rule selection, and rule performance is assessed separately for each category. Experiment 5 will test the hypothesis that untrained decision makers rely on concrete surface features, whereas trained desision makers rely on abstract structural principles for categorizing decision situations. Experiment 6 will investigate how individuals learn to discriminate rule performance on the basis of envirionmental cues. Overall, this research program will improve our understanding about the evolution of decision strategies, the development of both optimal and non-optimal strategies, and the process that novice decision makers use to become experts through practice.