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A model of plausibility

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>2/01/2006
<mark>Journal</mark>Cognitive Science
Issue number1
Volume30
Number of pages26
Pages (from-to)95-120
Publication StatusPublished
<mark>Original language</mark>English

Abstract

Plausibility has been implicated as playing a critical role in many cognitive phenomena from comprehension to problem solving. Yet, across cognitive science, plausibility is usually treated as an operationalized variable or metric rather than being explained or studied in itself. This article describes a new cognitive model of plausibility, the Plausibility Analysis Model (PAM), which is aimed at modeling human plausibility judgment. This model uses commonsense knowledge of concept-coherence to determine the degree of plausibility of a target scenario. In essence, a highly plausible scenario is one that fits prior knowledge well: with many different sources of corroboration, without complexity of explanation, and with minimal conjecture. A detailed simulation of empirical plausibility findings is reported, which shows a close correspondence between the model and human judgments. In addition, a sensitivity analysis demonstrates that PAM is robust in its operations.

Bibliographic note

2006 Lawrence Erlbaum Associates, Inc.