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Bayesian Nets and Causality: Philosophical and Computational Foundations
Oxford, England: Oxford University Press (2004)
Abstract
Bayesian nets are widely used in artificial intelligence as a calculus for causal reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover causal relationships. This book, aimed at researchers and graduate students in computer science, mathematics and philosophy, brings together two important research topics: how to automate reasoning in artificial intelligence, and the nature of causality and probability in philosophy.Author's Profile
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| manuscript | Williamson, Jon (manuscript) "Bayesian nets and causality". |
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Jon Williamson, bayesian nets and causality: Philosophical and computational foundations. [REVIEW]Bradford McCall - 2008 - Minds and Machines 18 (2):301-302.
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Citations of this work
Interpreting causality in the health sciences.Federica Russo & Jon Williamson - 2007 - International Studies in the Philosophy of Science 21 (2):157 – 170.
Mechanisms and the Evidence Hierarchy.Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo & Jon Williamson - 2014 - Topoi 33 (2):339-360.
The structure of epistemic probabilities.Nevin Climenhaga - 2020 - Philosophical Studies 177 (11):3213-3242.
Bayesian Epistemology.Stephan Hartmann & Jan Sprenger - 2010 - In Sven Bernecker & Duncan Pritchard (eds.), The Routledge Companion to Epistemology. New York: Routledge. pp. 609-620.
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