8 found
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  1.  52
    Facts and Possibilities: A Model‐Based Theory of Sentential Reasoning.Sangeet S. Khemlani, Ruth M. J. Byrne & Philip N. Johnson-Laird - 2018 - Cognitive Science 42 (6):1887-1924.
    This article presents a fundamental advance in the theory of mental models as an explanation of reasoning about facts, possibilities, and probabilities. It postulates that the meanings of compound assertions, such as conditionals (if) and disjunctions (or), unlike those in logic, refer to conjunctions of epistemic possibilities that hold in default of information to the contrary. Various factors such as general knowledge can modulate these interpretations. New information can always override sentential inferences; that is, reasoning in daily life is defeasible (...)
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  2.  62
    Naive Probability: Model‐Based Estimates of Unique Events.Sangeet S. Khemlani, Max Lotstein & Philip N. Johnson-Laird - 2015 - Cognitive Science 39 (6):1216-1258.
    We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, (...)
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  3.  34
    Illusions in Reasoning.Sangeet S. Khemlani & P. N. Johnson-Laird - 2017 - Minds and Machines 27 (1):11-35.
    Some philosophers argue that the principles of human reasoning are impeccable, and that mistakes are no more than momentary lapses in “information processing”. This article makes a case to the contrary. It shows that human reasoners commit systematic fallacies. The theory of mental models predicts these errors. It postulates that individuals construct mental models of the possibilities to which the premises of an inference refer. But, their models usually represent what is true in a possibility, not what is false. This (...)
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  4.  31
    Models of Possibilities Instead of Logic as the Basis of Human Reasoning.P. N. Johnson-Laird, Ruth M. J. Byrne & Sangeet S. Khemlani - 2024 - Minds and Machines 34 (3):1-22.
    The theory of mental models and its computer implementations have led to crucial experiments showing that no standard logic—the sentential calculus and all logics that include it—can underlie human reasoning. The theory replaces the logical concept of validity (the conclusion is true in all cases in which the premises are true) with necessity (conclusions describe no more than possibilities to which the premises refer). Many inferences are both necessary and valid. But experiments show that individuals make necessary inferences that are (...)
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  5.  40
    Episodes, events, and models.Sangeet S. Khemlani, Anthony M. Harrison & J. Gregory Trafton - 2015 - Frontiers in Human Neuroscience 9:159116.
    We describe a novel computational theory of how individuals segment perceptual information into representations of events. The theory is inspired by recent findings in the cognitive science and cognitive neuroscience of event segmentation. In line with recent theories, it holds that online event segmentation is automatic, and that event segmentation yields mental simulations of events. But it posits two novel principles as well: first, discrete episodic markers track perceptual and conceptual changes, and can be retrieved to construct event models. Second, (...)
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  6. Toward a Unified Theory of Reasoning.P. N. Johnson-Laird & Sangeet S. Khemlani - 2014 - The Psychology of Learning and Motivation.
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  7.  63
    Determinants of cognitive variability.Sangeet S. Khemlani, N. Y. Louis Lee & Monica Bucciarelli - 2010 - Behavioral and Brain Sciences 33 (2-3):37.
    Henrich et al. address how culture leads to cognitive variability and recommend that researchers be critical about the samples they investigate. However, there are other sources of variability, such as individual strategies in reasoning and the content and context on which processes operate. Because strategy and content drive variability, those factors are of primary interest, while culture is merely incidental.
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  8.  23
    The function and representation of concepts.Sangeet S. Khemlani & Geoffrey Goodwin - 2010 - Behavioral and Brain Sciences 33 (2-3):216-217.
    Machery has usefully organized the vast heterogeneity in conceptual representation. However, we believe his argument is too narrow in tacitly assuming that concepts are comprised of only prototypes, exemplars, and theories, and also that its eliminative aspect is too strong. We examine two exceptions to Machery's representational taxonomy before considering whether doing without concepts is a good idea.
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