|Abstract||How should we reason with causal relationships? Much recent work on this question has been devoted to the theses (i) that Bayesian nets provide a calculus for causal reasoning and (ii) that we can learn causal relationships by the automated learning of Bayesian nets from observational data. The aim of this book is to..|
|Keywords||No keywords specified (fix it)|
|Through your library||Only published papers are available at libraries|
Similar books and articles
Bradford McCall (2008). Jon Williamson, Bayesian Nets and Causality: Philosophical and Computational Foundations. Minds and Machines 18 (2).
Kevin B. Korb (2007). Jon Williamson. Bayesian Nets and Causality: Philosophical and Computational Foundations. Philosophia Mathematica 15 (3):389-396.
Clark Glymour (2009). Jon Williamson Bayesian Nets and Causality. British Journal for the Philosophy of Science 60 (4):849-855.
Jon Williamson (2004). Bayesian Nets and Causality: Philosophical and Computational Foundations. OUP Oxford.
Matt Williams & Jon Williamson (2006). Combining Argumentation and Bayesian Nets for Breast Cancer Prognosis. Journal of Logic, Language and Information 15 (1-2).
Added to index2009-01-28
Total downloads13 ( #87,888 of 549,065 )
Recent downloads (6 months)1 ( #63,185 of 549,065 )
How can I increase my downloads?