Quantum Information Processing Explanation for Interactions between Inferences and Decisions

Jerome R. Busemeyer , Zheng Wang

Markov and quantum information processing models are compared with respect to their capability of explaining two different puzzling findings from empirical research on human inference and decision making. Both findings involve a task that requires making an inference about one of two possible uncertain states, followed by decision about two possible courses of action. Two conditions are compared: under one condition, the decisions are obtained after discovering or measuring the uncertain state; under another condition, choices are obtained before resolving the uncertainty so that the state remains unknown or unmeasured. Systematic departures from the Markov model are observed, and these deviations are explained as interference effects using the quantum model.

Subjects: 15.5 Decision Theory; 3.4 Probabilistic Reasoning

Submitted: Jan 25, 2007


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