Connections among Decision Field Theory models of cognition

Sequential sampling process models provide promising approaches to characterizing human judgment and decision making. In this paper, we study one class of sequential sampling process models referred to as Decision Field Theory (DFT). These models not only provide qualitative explanations of empirical findings, but also provide quantitative predictions of real time performance. We analyze major DFT models in the literature, and demonstrate that models which are seemingly similar can behave very differently, depending upon the cognitive basis for model parameters. Based on this analysis, we propose a mathematical framework which attempts to unify DFT models. ⺠We discuss the similarities and differences among Decision Field Theory (DFT) models. ⺠We develop a unified mathematical framework for DFT models. ⺠We study differences between sequential processing and parallel processing models. ⺠We conduct a series of simulation studies.