Measuring causal interaction in bayesian networks
|Abstract||Artificial Intelligence (AI) and Philosophy of Science share a fundamental problem—understanding causality. Bayesian networks have recently been used by Judea Pearl in a new approach to understanding causality (Pearl, 2000). Part of understanding causality is understanding causal interaction. Bayes nets can represent any degree of causal interaction, and researchers normally try to limit interactions, usually by replacing the full CPT with a noisy-OR function. But we show that noisy-OR and another common model are merely special cases of the general linear systems definition of noninteraction. However, they apply in different situations, and we can measure the degree of causal interaction relative to any such model.|
|Keywords||No keywords specified (fix it)|
|Categories||No categories specified (fix it)|
|External links||This entry has no external links. Add one.|
|Through your library||Only published papers are available at libraries|
Similar books and articles
Peter Spirtes (2011). Intervention, Determinism, and the Causal Minimality Condition. Synthese 182 (3):335-347.
Charles R. Twardy & Kevin B. Korb (2004). A Criterion of Probabilistic Causation. Philosophy of Science 71 (3):241-262.
Jon Williamson (2004). A Dynamic Interaction Between Machine Learning and the Philosophy of Science. Minds and Machines 14 (4):539-549.
Toby Handfield, Charles R. Twardy, Kevin B. Korb & Graham Oppy (2008). The Metaphysics of Causal Models: Where's the Biff? Erkenntnis 68 (2):149-68.
Jon Williamson (2004). Bayesian Nets and Causality: Philosophical and Computational Foundations. OUP Oxford.
Douglas Ehring (1986). Causal Processes and Causal Interactions. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:24 - 32.
Donald Gillies (2002). Causality, Propensity, and Bayesian Networks. Synthese 132 (1-2):63 - 88.
Added to index2009-01-28
Total downloads5 ( #160,171 of 548,972 )
Recent downloads (6 months)0
How can I increase my downloads?