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Probabilistic networks and expert systems / Cowell , Robert G. ; Dawid , Philip A.

Public ISBD Titre : Probabilistic networks and expert systems Type de document : texte imprimé Auteurs : Cowell , Robert G., Auteur ; Dawid , Philip A., Auteur ; Lauritzen , Steffen, Auteur Editeur : Berlin : Springer Année de publication : 1999 Collection : Statistics for engineering and information science Importance : XII-321 p. Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : 978-0-387-98767-5 Note générale : Bibliogr. p. [281]-305. Index Langues : Anglais (eng) Mots-clés : Probabilities Expert  systems  (Computer  science) Probabilités Systèmes  experts  (informatique) Intelligence  artificielle  --  Méthodes  statistiques Index. décimale : 681.3.02 Conception,construction et structures des systèmes machines et éléments de traitement de données.(Conception des systèmes) Résumé : Probabilistic expert systems are graphical networks that support the modelling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors over a number of years, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures and algorithms, emphasizing those cases in which exact answers are obtainable. It covers both the updating of probabilistic uncertainty in the light of new evidence, and statistical inference, about unknown probabilities or unknown model structure, in the light of new data. The book will be of interest to researchers and graduate students in artificial intelligence who desire an understanding of the mathematical and statistical basis of probabilistic expert systems, and to students and research workers in statistics wanting an introduction to this fascinating and rapidly developing field. The careful attention to detail will also make this work an important reference source for all those involved in the theory and applications of probabilistic expert systems Note de contenu : - Logic, Uncertainty, and Probability - Building and Using Probabilistic Networks - Graph Theory - Discrete Networks - Gaussian and Mixed Discrete-Gaussian Networks - Discrete Multistage Decision Networks - Learning About Probabilities - Checking Models Against Data - Structural Learning A Conjugate Analysis for Discrete Data B Gibbs Sampling C Information and Software on the World Wide Web Probabilistic networks and expert systems [texte imprimé] / Cowell , Robert G., Auteur ; Dawid , Philip A., Auteur ; Lauritzen , Steffen, Auteur . - Springer, 1999 . - XII-321 p. : ill. ; 24 cm. - (Statistics for engineering and information science) . ISBN : 978-0-387-98767-5 Bibliogr. p. [281]-305. Index Langues : Anglais (eng) Mots-clés : Probabilities Expert  systems  (Computer  science) Probabilités Systèmes  experts  (informatique) Intelligence  artificielle  --  Méthodes  statistiques Index. décimale : 681.3.02 Conception,construction et structures des systèmes machines et éléments de traitement de données.(Conception des systèmes) Résumé : Probabilistic expert systems are graphical networks that support the modelling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors over a number of years, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures and algorithms, emphasizing those cases in which exact answers are obtainable. It covers both the updating of probabilistic uncertainty in the light of new evidence, and statistical inference, about unknown probabilities or unknown model structure, in the light of new data. The book will be of interest to researchers and graduate students in artificial intelligence who desire an understanding of the mathematical and statistical basis of probabilistic expert systems, and to students and research workers in statistics wanting an introduction to this fascinating and rapidly developing field. The careful attention to detail will also make this work an important reference source for all those involved in the theory and applications of probabilistic expert systems Note de contenu : - Logic, Uncertainty, and Probability - Building and Using Probabilistic Networks - Graph Theory - Discrete Networks - Gaussian and Mixed Discrete-Gaussian Networks - Discrete Multistage Decision Networks - Learning About Probabilities - Checking Models Against Data - Structural Learning A Conjugate Analysis for Discrete Data B Gibbs Sampling C Information and Software on the World Wide Web

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Code-barres	Cote	Support	Localisation	Section	Disponibilité	Etat_Exemplaire
046361	681.3.02 PRO	Papier	Bibliothèque Centrale	Informatique	Disponible	Consultation sur place