Synthese 193 (4):1107-1126 (2016)
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Abstract |
Causal Bayes nets have been developed in philosophy, statistics, and computer sciences to provide a formalism to represent causal structures, to induce causal structure from data and to derive predictions. Causal Bayes nets have been used as psychological theories in at least two ways. They were used as rational, computational models of causal reasoning and they were used as formal models of mental causal models. A crucial assumption made by them is the Markov condition, which informally states that variables are independent of other variables that are not their direct or indirect effects conditional on their immediate causes. Whether people’s inferences conform to the causal Markov and the faithfulness condition has recently been investigated empirically. A review of respective research indicates that inferences frequently violate these conditions. This finding challenges some uses of causal Bayes nets in psychology. They entail that causal Bayes nets may not be appropriate to derive predictions for causal model theories of causal reasoning. They also question whether causal Bayes nets as a rational model are empirically descriptive. They do not challenge, however, causal Bayes nets as normative models and their usage as formal models of causal reasoning
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Keywords | Causal Bayes nets Rational models Psychological theories Causal learning and reasoning Empirical research |
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DOI | 10.1007/s11229-015-0734-0 |
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References found in this work BETA
Scientific Explanation and the Causal Structure of the World.Wesley C. Salmon - 1984 - Princeton University Press.
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.Judea Pearl - 1988 - Morgan Kaufmann.
Review: The Grand Leap; Reviewed Work: Causation, Prediction, and Search. [REVIEW]Peter Spirtes, Clark Glymour & Richard Scheines - 1996 - British Journal for the Philosophy of Science 47 (1):113-123.
A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.Alison Gopnik, Clark Glymour, Laura Schulz, Tamar Kushnir & David Danks - 2004 - Psychological Review 111 (1):3-32.
Causal Models: How People Think About the World and its Alternatives.Steven A. Sloman - 2005 - Oxford, England: OUP.
View all 31 references / Add more references
Citations of this work BETA
Clark Glymour’s Responses to the Contributions to the Synthese Special Issue “Causation, Probability, and Truth: The Philosophy of Clark Glymour”.Clark Glymour - 2016 - Synthese 193 (4):1251-1285.
Introduction to the Special Issue “Causation, Probability, and Truth—the Philosophy of Clark Glymour”.Alexander Gebharter & Gerhard Schurz - 2016 - Synthese 193 (4):1007-1010.
A Process Model of Causal Reasoning.Zachary J. Davis & Bob Rehder - 2020 - Cognitive Science 44 (5).
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