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| Date: | Tue, March 4, 2014 |
| Time: | 11:15 |
| Place: | Research I Seminar Room |
Abstract: The 2N-ary choice tree (2NCT) model is an approach developed for multi-alternative and multi-attribute decision problems which takes into account both the dynamic and stochastic nature of decision making (Wollschläger & Diederich, 2012, Frontiers in Cognitive Science). Its goal is to describe the motivational and cognitive mechanisms that guide the deliberation process in decision making. The model is based on a random walk on a 2N-ary choice tree assigning two counters to each of the N alternatives. One counter samples information in favor of the choosing the respective alternative, the other counter samples information against choosing it; the difference in value between the counters describes the momentary preference state for the alternative. The update of counters - including all possible combinations of counter states - can be described in a graph theoretic structure, i.e., a (2N-ary) tree with vertices V and 2N children for each vertex. The information sampling process determining the preference strength for each choice option at each moment in time is reflected in the transition probabilities between vertices. The constituents are 1) a weighted comparison of choice alternatives, 2) a diminishing (leakage) of already sampled information over time, 3) inhibition and 4) a random component. Here, we focus on how choice probabilities and response times can be determined for optional and fixed stopping times and how the model can be implemented (with MATLAB).