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  1. Cognitive Processes Underlying Heuristic Decision Making.Sebastian Dummel - unknown
    Our life is full of choices—choices that differ, among others, in the amount of information on which they are based. For instance, when facing a choice between two options that differ on several decision-relevant attributes, one could rely on the most relevant attribute only to make the decision, or one could integrate information from several attributes and base the choice on that combined information. When a decision maker bases her choice on the most relevant attribute only, however, what does this (...)
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  • TTB vs. Franklin's Rule in Environments of Different Redundancy.Gerhard Schurz & Paul D. Thorn - 2014 - Frontiers in Psychology 5:15-16.
    This addendum presents results that confound some commonly made claims about the sorts of environments in which the performance of TTB exceeds that of Franklin's rule, and vice versa.
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  • Bottom-up model of strategy selection‖.Tomasz Smolen & Szymon Wichary - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society.
     
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  • Attractivity Weighting: Take-the-Best's Foolproof Sibling.Paul D. Thorn & Gerhard Schurz - 2016 - In A. Papafragou, D. Grodner, D. Mirman & J. C. Trueswell (eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 432-437) Cognitive Science Society. Cognitive Science Society. pp. 456-461.
    We describe a prediction method called "Attractivity Weighting" (AW). In the case of cue-based paired comparison tasks, AW's prediction is based on a weighted average of the cue values of the most successful cues. In many situations, AW's prediction is based on the cue value of the most successful cue, resulting in behavior similar to Take-the-Best (TTB). Unlike TTB, AW has a desirable characteristic called "access optimality": Its long-run success is guaranteed to be at least as great as the most (...)
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