Psychological models for two-choice decision tasks typically model the probability that a particular response is made at time t via the first-passage time to an absorbing boundary for some stochastic process. In contrast to the most commonly used models which use classical random walks for the underlying process, a recent paper by Busemeyer, Wang, and Townsend (2006) proposed that quantum walks may provide an interesting alternative. In this paper, we extend this work by introducing a class of partially-coherent quantum walk models that can be applied to human two-choice tasks. The models trace out a path from quantum to classical models, preserving some of the desirable features of both. We discuss the properties of these models, and the implications for modeling simple decisions.Ian G. Fuss and Daniel J. Navarr
