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The Dempster-Shafer Theory of Evidence as a Model of Human Decision Making

Abstract

Many psychology researchers have shown that humans do not process probabilistic information in a manner consistent with Bayes' theory [9, 10, 16, 24, 23, 27]. Robinson and Hastie [24, 23] showed that humans made non-compensatory probability updates, produced super-additive distributions, and resuscitated zero probability possibilities. While most researchers have classified these behaviors as nonnormative, we found that the Dempster-Shafer theory could model each of these behaviors in a normative and theoretically sound fashion. While not claiming that the theory modeb human processes, we claim that the similarities should aid user acceptance of Dempster-Shafer based decision systems.

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