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A Computational Model for Constructing Preferences for Multiple Choice Options

Abstract

When choosing between multiple alternatives, people usuallydo not have ready-made preferences in their mind but ratherconstruct them on the go. The 2N-ary Choice Tree Model(Wollschlaeger & Diederich, 2012) proposes a preference con-struction process for N choice options from description, whichis based on attribute weights, differences between attribute val-ues, and noise. It is able to produce similarity, attraction,and compromise effects, which have become a benchmark formulti-alternative choice models, but also several other contextand reference point effects. Here, we present a new and math-ematically tractable version of the model – the Simple ChoiceTree Model – which also explains the above mentioned effectsand additionally accounts for the positive correlation betweenthe attraction and compromise effect, and the negative correla-tion between these two and the similarity effect as observed byBerkowitsch, Scheibehenne, and Rieskamp (2014).

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