Review: Models of Human Probability Judgment Errors

Abstract

One of cognitive science's core challenges is reconciling the success of probabilistic models in explaining human cognition with the observed inconsistencies in human probability judgments. This review delves into models that address this discrepancy, shedding light on probabilistic fallacies. It encompasses earlier concepts like heuristics and averaging models, as well as contemporary, comprehensive models like quantum probability, the "probability plus noise" model, and the Bayesian sampler.

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