Probabilistic Networks and Expert Systems by Robert G. Cowell, A. Philip Dawid, Steffen L. Lauritzen,

By Robert G. Cowell, A. Philip Dawid, Steffen L. Lauritzen, David J. Spiegelhalter (auth.)

Winner of the 2002 DeGroot Prize.

Probabilistic specialist structures are graphical networks that aid the modelling of uncertainty and judgements in huge complicated domain names, whereas maintaining ease of calculation. development on unique study by way of the authors over a couple of years, this publication supplies a radical and rigorous mathematical therapy of the underlying rules, constructions, and algorithms, emphasizing these situations during which designated solutions are accessible. It covers either the updating of probabilistic uncertainty within the mild of recent proof, and statistical inference, approximately unknown percentages or unknown version constitution, within the mild of recent information. The cautious consciousness to element will make this paintings a tremendous reference resource for all these excited about the idea and purposes of probabilistic professional systems.

This e-book used to be offered the 1st DeGroot Prize by means of the overseas Society for Bayesian research for a booklet making a tremendous, well timed, thorough, and particularly unique contribution to the information literature.

Robert G. Cowell is a Lecturer within the college of Actuarial technological know-how and assurance of the Sir John Cass company institution, urban of London. He has been engaged on probabilistic specialist structures when you consider that 1989.

A. Philip Dawid is Professor of facts at Cambridge college. He has served as Editor of the Journal of the Royal Statistical Society (Series B), Biometrika and Bayesian Analysis, and as President of the foreign Society for Bayesian research. He holds the Royal Statistical Society man Medal in Bronze and in Silver, and the Snedecor Award for the easiest booklet in Biometry.

Steffen L. Lauritzen is Professor of records on the collage of Oxford. He has served as Editor of the Scandinavian magazine of Statistics. He holds the Royal Statistical Society man Medal in Silver and is an Honorary Fellow of a similar society. He has, together with David J. Spiegelhalter, got the yank Statistical Association’s award for an "Outstanding Statistical Application."

David J. Spiegelhalter is Winton Professor of the general public realizing of possibility at Cambridge college and Senior Scientist within the MRC Biostatistics Unit, Cambridge. He has released generally on Bayesian technique and functions, and holds the Royal Statistical Society man Medal in Bronze and in Silver.

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Extra resources for Probabilistic Networks and Expert Systems

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Let K be a chain graph having the set of chain components K. Then, instead of selecting a parentless node for deletion, one selects a parentless chain component, that is a chain component none of whose nodes have parents. The result is a well-ordering of the chain components. 5 is (A, B, {C, D}, E, F ); yet another is (E, B, A, {C, D}, F ). Given a chain graph, the set of vertices α such that α → β but not β → α is the set an(β) of the ancestors of β, and the descendants de(α) of α are the vertices β such that α → β but not β → α.

10 A broader context for probabilistic expert systems 23 Intelligence, which hosts an excellent Web page providing many relevant links, and provides a forum for discussion of a wide range of issues concerning uncertainty in expert systems (although the arguments between the advocates of probabilistic and non-probabilistic approaches appear to have died down as each group tries to identify the most appropriate domains for its work). Other electronic sources of information include the Bayesian network Web page of the US Air Force Institute of Technology Artificial Intelligence Laboratory, which in particular features informal comments of people who work in industry, and the Web page of the Microsoft Decision Theory and Adaptive Systems group.

05 would like to know the chance that each of these diseases is present, and if tuberculosis were ruled out by another test, how would that change the belief in lung cancer? Also, would knowing smoking history or getting an X-ray contribute more information about cancer, given that smoking may ‘explain away’ the dyspnoea since bronchitis is considered a possibility? Finally, when all information is in, can we identify which was the most influential in forming our judgement? 10 A broader context for probabilistic expert systems We have informally introduced the idea of representing qualitative relationships between variables by graphs and superimposing a joint probability model on the unknown quantities.

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