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Modeling probability knowledge and choice in decisions from experience


Hawkins, GE and Camilleri, AR and Heathcote, A and Newell, BR and Brown, SD, Modeling probability knowledge and choice in decisions from experience, Proceedings of the 36th Annual Conference of the Cognitive Science Society, 23-26 July, 2014, Quebec City, Canada, pp. 1-6. ISSN 1069-7977 (2014) [Refereed Conference Paper]

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In most everyday decisions we learn about the outcomes of alternative courses of action through experience: a sampling process. Current models of these decisions from experience do not explain how the sample outcomes are used to form a representation of the distribution of outcomes. We overcome this limitation by developing a new and simple model, the Exemplar Confusion (ExCon) model. In a novel experiment, the model predicted participantsí choices and their knowledge of outcome probabilities, when choosing among multiple-outcome gambles in sampling and feedback versions of the task. The model also performed at least as well as other leading choice models when evaluated against benchmark data from the Technion Prediction Tournament. Our approach advances current understanding by proposing a psychological mechanism for how probability estimates arise rather than using estimates solely as inputs to choice models.

Item Details

Item Type:Refereed Conference Paper
Keywords:Experience-based choice; Probability estimation; Sampling; Feedback; Exemplar model
Research Division:Psychology
Research Group:Cognitive and computational psychology
Research Field:Decision making
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in psychology
UTAS Author:Heathcote, A (Professor Andrew Heathcote)
ID Code:99362
Year Published:2014
Deposited By:Medicine
Deposited On:2015-03-23
Last Modified:2017-10-31

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