The authors interpret decision field theory (J. R. Busemeyer & J. T. Townsend, 1993) as a connectionist network and extend it to accommodate multialternative preferential choice situations. This article shows that the classic weighted additive utility model (see R. L. Keeney & H. Raiffa, 1976) and the classic Thurstone preferential choice model (see L. L. Thurstone, 1959) are special cases of this new multialternative decision field theory (MDFT), which also can emulate the search process of the popular elimination by aspects (EBA) model (see A. Tversky, 1969). The new theory is unique in its ability to explain several central empirical results found in the multialternative preference literature with a common set of principles. These empirical results include the similarity effect, the attraction effect, and the compromise effect, and the complex interactions among these three effects. The dynamic nature of the model also implies strong testable predictions concerning the moderating effect of time pressure on these three effects.

Using a probabilistic category learning paradigm, 6 experiments explored irrelevant information and 4 current models. Utilization of relevant configural information was lowered by the presence of an irrelevant dimension, both if that was the only relevant information and if a dimension was also relevant. An irrelevant cue value lowered the utilization of relevant cue values. An additional relevant dimension had a larger degrading effect on the utilization of a relevant dimension than an additional irrelevant dimension, thereby suggesting that the effect of irrelevant information is due to the complexity of the environment rather than to factors particular to the irrelevant nature of the information. The current models failed to fit the findings. However, results showing that memory errors account for salience effects provide a direction for revising one of the models.

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