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A model of plausibility

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A model of plausibility. / Connell, Louise; Keane, Mark T.

In: Cognitive Science, Vol. 30, No. 1, 02.01.2006, p. 95-120.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Connell, L & Keane, MT 2006, 'A model of plausibility', Cognitive Science, vol. 30, no. 1, pp. 95-120. https://doi.org/10.1207/s15516709cog0000_53

APA

Connell, L., & Keane, M. T. (2006). A model of plausibility. Cognitive Science, 30(1), 95-120. https://doi.org/10.1207/s15516709cog0000_53

Vancouver

Connell L, Keane MT. A model of plausibility. Cognitive Science. 2006 Jan 2;30(1):95-120. https://doi.org/10.1207/s15516709cog0000_53

Author

Connell, Louise ; Keane, Mark T. / A model of plausibility. In: Cognitive Science. 2006 ; Vol. 30, No. 1. pp. 95-120.

Bibtex

@article{1899b634238a42a88b2db4a510c43b04,
title = "A model of plausibility",
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.",
keywords = "Psychology, Cognition , Reasoning , Plausibility , Computer simulation , Symbolic , computational modeling",
author = "Louise Connell and Keane, {Mark T.}",
note = "2006 Lawrence Erlbaum Associates, Inc.",
year = "2006",
month = jan,
day = "2",
doi = "10.1207/s15516709cog0000_53",
language = "English",
volume = "30",
pages = "95--120",
journal = "Cognitive Science",
issn = "0364-0213",
publisher = "Wiley-Blackwell",
number = "1",

}

RIS

TY - JOUR

T1 - A model of plausibility

AU - Connell, Louise

AU - Keane, Mark T.

N1 - 2006 Lawrence Erlbaum Associates, Inc.

PY - 2006/1/2

Y1 - 2006/1/2

N2 - 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.

AB - 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.

KW - Psychology

KW - Cognition

KW - Reasoning

KW - Plausibility

KW - Computer simulation

KW - Symbolic

KW - computational modeling

U2 - 10.1207/s15516709cog0000_53

DO - 10.1207/s15516709cog0000_53

M3 - Journal article

C2 - 21702810

VL - 30

SP - 95

EP - 120

JO - Cognitive Science

JF - Cognitive Science

SN - 0364-0213

IS - 1

ER -