Decision field theory (Busemeyer & Townsend, 1993) is interpreted as an artificial neural network and extended to accommodate multi-alternative preferential choice situations. The classic weighted additive utility model and the classic Thurstone preferential choice model are shown to be special cases of the new theory, and the proposed theory also can emulate the search process of the popular elimination by aspects model. The new theory explains several central empirical results found in the multi-alternative preference literature, including the similarity effect, the attraction effect, and the compromise effect. Furthermore, it is the only formal theory that has succeeded in explaining the complex interactions among these three effects. The dynamic nature of the model also allows strong testable predictions as to the effect of time pressure on these three effects.
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