Probabilistic Methods In Expert Systems
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Probabilistic Expert Systems
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Author : Glenn Shafer
language : en
Publisher: SIAM
Release Date : 1996-01-01
Probabilistic Expert Systems written by Glenn Shafer and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-01-01 with Computers categories.
Probabilistic Expert Systems emphasizes the basic computational principles that make probabilistic reasoning feasible in expert systems. The key to computation in these systems is the modularity of the probabilistic model. Shafer describes and compares the principal architectures for exploiting this modularity in the computation of prior and posterior probabilities. He also indicates how these similar yet different architectures apply to a wide variety of other problems of recursive computation in applied mathematics and operations research. The field of probabilistic expert systems has continued to flourish since the author delivered his lectures on the topic in June 1992, but the understanding of join-tree architectures has remained missing from the literature. This monograph fills this void by providing an analysis of join-tree methods for the computation of prior and posterior probabilities in belief nets. These methods, pioneered in the mid to late 1980s, continue to be central to the theory and practice of probabilistic expert systems. In addition to purely probabilistic expert systems, join-tree methods are also used in expert systems based on Dempster-Shafer belief functions or on possibility measures. Variations are also used for computation in relational databases, in linear optimization, and in constraint satisfaction. This book describes probabilistic expert systems in a more rigorous and focused way than existing literature, and provides an annotated bibliography that includes pointers to conferences and software. Also included are exercises that will help the reader begin to explore the problem of generalizing from probability to broader domains of recursive computation.
Probabilistic Methods In Expert Systems
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Author : Romano Scozzafava
language : en
Publisher:
Release Date : 1993
Probabilistic Methods In Expert Systems written by Romano Scozzafava and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Expert systems (Computer science) categories.
Expert Systems And Probabilistic Network Models
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Author : Enrique Castillo
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Expert Systems And Probabilistic Network Models written by Enrique Castillo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.
Probabilistic Reasoning In Expert Systems
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Author : Richard E. Neapolitan
language : en
Publisher: Wiley-Interscience
Release Date : 1990-03-16
Probabilistic Reasoning In Expert Systems written by Richard E. Neapolitan and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-03-16 with Computers categories.
Addresses the use probability theory as a tool for designing with and implementing uncertainity reasoning. Provides many concrete algorithms, explores techniques for solving multimembership classification problems not based directly on causal networks, and offers practical recommendations, matching specific methods with sample expert systems.
Probabilistic Networks And Expert Systems
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Author : Robert G. Cowell
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-16
Probabilistic Networks And Expert Systems written by Robert G. Cowell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-16 with Computers categories.
Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.
Uncertain Information Processing In Expert Systems
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Author : Petr Hajek
language : en
Publisher: CRC Press
Release Date : 1992-06-29
Uncertain Information Processing In Expert Systems written by Petr Hajek and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-06-29 with Computers categories.
Uncertain Information Processing in Expert Systems systematically and critically examines probabilistic and rule-based (compositional, MYCIN-like) systems, the two most important families of expert systems dealing with uncertainty. The book features a detailed introduction to probabilistic systems (including methods using graphical models and methods of knowledge integration), an analysis of compositional systems based on algebraic considerations, an application of graphical models, and the Dempster-Shafer theory of evidence and its use in expert systems. The book will be useful to anyone working in artificial intelligence, statistical computing, symbolic logic, and expert systems.
Probabilistic Networks And Expert Systems
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Author : Robert G. Cowell
language : en
Publisher: Springer
Release Date : 2007-07-25
Probabilistic Networks And Expert Systems written by Robert G. Cowell and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-25 with Mathematics categories.
Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.
Knowledge Integration Methods For Probabilistic Knowledge Based Systems
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Author : Van Tham Nguyen
language : en
Publisher: CRC Press
Release Date : 2022-12-30
Knowledge Integration Methods For Probabilistic Knowledge Based Systems written by Van Tham Nguyen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Business & Economics categories.
Knowledge-based systems and solving knowledge integrating problems have seen a great surge of research activity in recent years. Knowledge Integration Methods provides a wide snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency, and methods for integrating knowledge bases. The book also provides the mathematical background to solving problems of restoring consistency and integrating probabilistic knowledge bases in the integrating process. The research results presented in the book can be applied in decision support systems, semantic web systems, multimedia information retrieval systems, medical imaging systems, cooperative information systems, and more. This text will be useful for computer science graduates and PhD students, in addition to researchers and readers working on knowledge management and ontology interpretation.
Expert Systems
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Author : Peter S. Sell
language : en
Publisher: Wiley
Release Date : 1985
Expert Systems written by Peter S. Sell and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Computers categories.
A concise practical introduction to the history, characteristics, structure, operation, and use of expert systems. Provides programmers with sufficient insight and guidance to enable them to construct an expert system shell using a favorite programming language. Shows how to develp and maintain expert systems, and how to tackle technical problems unique to the field. There's also advice on how to access new applications.
Uncertainty And Vagueness In Knowledge Based Systems
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Author : Rudolf Kruse
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Uncertainty And Vagueness In Knowledge Based Systems written by Rudolf Kruse and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence. It puts particular emphasis on a thorough analysis of these phenomena and on the development of sound mathematical modeling approaches. Beyond this theoretical basis the scope of the book includes also implementational aspects and a valuation of existing models and systems. The fundamental ambition of this book is to show that vagueness and un certainty can be handled adequately by using measure-theoretic methods. The presentation of applicable knowledge representation formalisms and reasoning algorithms substantiates the claim that efficiency requirements do not necessar ily require renunciation of an uncompromising mathematical modeling. These results are used to evaluate systems based on probabilistic methods as well as on non-standard concepts such as certainty factors, fuzzy sets or belief functions. The book is intended to be self-contained and addresses researchers and practioneers in the field of knowledge based systems. It is in particular suit able as a textbook for graduate-level students in AI, operations research and applied probability. A solid mathematical background is necessary for reading this book. Essential parts of the material have been the subject of courses given by the first author for students of computer science and mathematics held since 1984 at the University in Braunschweig.