Mathematical Models for Handling Partial Knowledge in Artificial Intelligence / Edition 1

Mathematical Models for Handling Partial Knowledge in Artificial Intelligence / Edition 1

by Giulianella Coletti, Didier Dubois, R. Scozzafava

ISBN-10: 0306450763

ISBN-13: 9780306450761

Pub. Date: 02/07/2008

Publisher: Springer US

Product Details

Springer US
Publication date:
Language of Science Series
Edition description:
Product dimensions:
7.01(w) x 10.00(h) x 0.03(d)

Table of Contents

Invited Papers: Ellsberg Paradox Intuition and Choquet Expected Utility (A. Chateauneuf). Fuzzy Logic as Logic (P. Hájek). Mathematical Foundations of Evidence Theory (J. Kohlas). Semantics for Uncertain Inference Based on Statistical Knowledge (H.E. Kyburg). Prospects and Problems in Applying the Fundamental Theorem of Prevision as an Expert System: An Example of Learning about Parole Decisions (F. Lad, I. Coope). Coherent Prevision as a Linear Functional without an Underlying Measure Space: The Purely Arithmetic Structure of Logical Relations among Conditional Quantities (F. Lad). Revision Rules for Convex Sets of Probabilities (S. Moral, N. Wilson). Contributed Papers: Generalized Concept of Atoms for Conditional Events (A. Capotorti). Checking the Coherence of Conditional Probabilities in Expert Systems: Remarks and Algorithms (G. Di Biase, A. Maturo). A Hyperstructure of Conditional Events for Artificial Intelligence (S. Doria, A. Maturo). Possibilistic Logic and Plausible Inference (D. Dubois, H. Prade). Probability Logic as a Fuzzy Logic (G. Gerla). Algorithms for Precise and Imprecise Conditional Probability Assessments (A. Gilio). A Valuationbased Architecture for Assumptionbased Reasoning (R. Haenni). 6 additional articles. Index.

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