Dynamic-stochastic decision models for multiple alternatives with multiple attributes

• Applicant: Professorin Dr. Adele Diederich
• Subject Area: General, Cognitive and Mathematical Psychology
• Term: from 2014 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 260116805

Dynamic-stochastic models, based on the notion of sequential sampling, are commonly used to predict choice behavior and response times in many areas of psychology, from basic perceptual tasks to multidimensional preference and decision making. Typically, these models can only account for binary decisions and unidimensional stimuli. However, many applications require an extension of the sequential sampling mechanism to multi-attribute choice options with multiple alternatives. Formal derivation of model predictions for more complex situations is often difficult or impossible, severely limiting the psychological interpretability and experimental tests of these models. An exception is Multiattribute Decision Field Theory (MDFT), developed in Diederich (1997), based on a matrix approximation of continuous processes, but up to now it has been developed only for binary choices and a pre-determined serial order of attribute processing.The goal of this project is to advance the sequential sampling approach within the class of dynamic-stochastic decision models. To this end, (1) we extend MDFT to include a variety of mechanisms for attribute handling (fixed and random processing order, switching times, and process durations) that constitute different hypotheses about the distribution of attention in stimulus processing. Then follows (2) the development of a decision model for multiple-choice options (Box model) that retains important features of MDFT. Analytical solutions for all models will be strived for.The empirical part of the project will experimentally probe several generalized versions of MDFT. We will explore different aspects of attribute processing in discrimination and choice paradigms. The first series of experiments will test hypotheses about the effect of payoffs, considered as stimulus attribute, on response frequencies in two different perceptual discrimination tasks. The effect of temporal distribution of information on task performance will be studied in a second series of experiments. Finally, the effect of the number of attributes on preference under risk will be investigated in a third experimental series.

• DFG Programme: Research Grants
• Participating Person: Privatdozent Keivan Mallahi-Karai, Ph.D.