This chapter presents a connectionist or artificial neural network approach to decision making. An essential idea of this approach is that decisions are based on the accumulation of the affective evaluations produced by each action until a threshold criterion is reached. This type of sequential sampling process forms the basis for decision making in a wide variety of other cognitive tasks such as perception, categorization, and memory. We apply these concepts to several important preferential choice phenomena, including similarity effects, attraction effects, compromise effects, loss aversion effects, and preference reversals. These analyses indicate that a relatively complex model of an individual’s choice process reveals a relatively simple representation of the individual’s underlying value structure.
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