Dynamic Stochastic Models for Decision Making under Time Constraints

This paper introduces the multiattribute dynamic decision model (MADD) to describe both the dynamic and the stochastic nature of decision making. MADD is based on information processing models developed by Diederich. It belongs to the class of sequential comparison models and generalizes and extends the so-called decision field theory (DFT) of Busemeyer and Townsend. Describing the decision maker's choice behavior for multiattribute choice alternatives in an uncertain environment by a stochastic process, the Ornstein-Uhlenbeck process, MADD predicts choice probabilities and mean choice response times when the decision maker has to respond within a given time limit. This paper outlines the prediction of two different versions of the model in detail. Copyright 1997 Academic Press

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