Conditional Logic in Expert Systems
Elsevier (Publisher)
Published in December 1991
Book
Hardback
356 pages
978-0-444-88819-8 (ISBN)
Description
This volume is a collection of invited papers on all basic aspects of conditional logic, inference and reasoning in expert systems. Specifically, theoretical results and applications centered around the main task in automated reasoning, namely conditional inference, in the three main approaches to reasoning under uncertainty (Bayesian, Fuzzy sets and Belief functions) including: - Measure-free conditioning, conditioning operators for non-monotonic reasoning; - General approach using logic to conditional inference; - Conditioning reasoning with fuzzy sets; - Random set as a formalism for evidential reasoning; - New results in the theory of Belief functions; - Some aspects of applications to various fields of AI.
This volume is a collection of invited papers on all basic aspects of conditional logic, inference and reasoning in expert systems. Specifically, theoretical results and applications centered around the main task in automated reasoning, namely conditional inference, in the three main approaches to reasoning under uncertainty (Bayesian, Fuzzy sets and Belief functions) including: - Measure-free conditioning, conditioning operators for non-monotonic reasoning; - General approach using logic to conditional inference; - Conditioning reasoning with fuzzy sets; - Random set as a formalism for evidential reasoning; - New results in the theory of Belief functions; - Some aspects of applications to various fields of AI.
This volume is a collection of invited papers on all basic aspects of conditional logic, inference and reasoning in expert systems. Specifically, theoretical results and applications centered around the main task in automated reasoning, namely conditional inference, in the three main approaches to reasoning under uncertainty (Bayesian, Fuzzy sets and Belief functions) including: - Measure-free conditioning, conditioning operators for non-monotonic reasoning; - General approach using logic to conditional inference; - Conditioning reasoning with fuzzy sets; - Random set as a formalism for evidential reasoning; - New results in the theory of Belief functions; - Some aspects of applications to various fields of AI.
More details
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 230 mm
ISBN-13
978-0-444-88819-8 (9780444888198)
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Schweitzer Classification
Content
Algebraic and Probabilistic Bases for Fuzzy Sets and the Development of Fuzzy Conditioning (I.R. Goodman). Deduction and Inference Using Conditional Logic and Probability (P.G. Calabrese). A Simple Look at Conditional Events (E.A. Walker). Conditioning, Non-Monotonic Logic, and Non-Standard Uncertainty Models (D. Dubois and H. Prade). Conditioning Operators in a Logic of Conditionals ( H.T. Nguyen and G.S. Rogers). Combination of Evidence with Conditional Objects and its Application to Cognitive Modeling (M. Spies). Connectives (and, or, not) and T-Operators in Fuzzy Reasoning (M.M. Gupta and J. Qi). Implication and Modus Ponens in Fuzzy Logic (P. Smets). Belief Function Computations (H.M. Thoma). A Random Set Formalism for Evidential Reasoning (K. Hestir, H.T. Nguyen, G.S. Rogers).