Belief change is an emerging field of artificial intelligence and information science dedicated to the dynamics of information and the present book provides a state-of-the-art picture of its formal foundations. It deals with the addition, deletion and combination of pieces of information and, more generally, with the revision, updating and fusion of knowledge bases. The book offers an extensive coverage of, and seeks to reconcile, two traditions in the kinematics of belief that often ignore each other - the symbolic and the numerical (often probabilistic) approaches. Moreover, the work encompasses both revision and fusion problems, even though these two are also commonly investigated by different communities. Finally, the book presents the numerical view of belief change, beyond the probabilistic framework, covering such approaches as possibility theory, belief functions and convex gambles.
The work thus presents a unified view of belief change operators, drawing from a widely scattered literature embracing philosophical logic, artificial intelligence, uncertainty modelling and database systems. The material is a clearly organised guide to the literature on the dynamics of epistemic states, knowledge bases and uncertain information, suitable for scholars and graduate students familiar with applied logic, knowledge representation and uncertain reasoning.
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REVISING UPDATING AND COMBINING KNOWLEDGE
REVISION OF BELIEF SETS AND BELIEF BASES
HOW HARD IS IT TO REVISE A BELIEF BASE?
CONDITIONALS AND THE RAMSEY TEST
LOGICS FOR BELIEF BASE UPDATING
REASONING ABOUT MERGED INFORMATION
NUMERICAL REPRESENTATION OF UNCERTAINTY
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accepted Alchourron approach Artificial Intelligence assume assumption axiomatic axioms base revision scheme Bayesian belief base belief change belief function belief revision belief set classical closure Cn(A cognitive combination computational conjunctive consider consistent context convex set corresponding database defined Dempster rule denoted disjunctive Dubois and Prade entrenchment ordering epistemic entrenchment equivalent finite framework fuzzy set Gardenfors Gardenfors and Makinson Hansson Horn logic imperfect specification implies inconsistent information sources Jeffrey's rule Katsuno and Mendelzon knowledge meet base revision merging modal logic models Nebel original belief P-complete partial meet contraction plausible polynomial polynomial hierarchy possibilistic possibility distribution possibility theory possible worlds postulates priority classes probabilistic probability measure probability theory problem propositional logic propositions Ramsey test reasoning relation representation revision formula revision operations Rott rule of conditioning satisfies Section selection function semantic sentences situations Smets subset THEOREM tion transferable belief model uncertainty update operations Winslett
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