Abstract
Decision making has long been of interest as a descriptive phenomenon in psychology and as a generative one in artificial intelligence. Research ranges from general, descriptive models of heuristic decision making to detailed studies of decision parameters. This paper introduces a model that formalizes and integrates several descriptive models so that it can serve both as a framework for psychological models and as an algorithm for computational decision making. We set special focus on the instantiation of this model with respect to aggregating cue values by reviewing some methods from the field of computational social choice. To show its applicability in the context of artificial intelligence we present a case study of computational problem solving.
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