Overview

""Frontiers in Belief Revision"" is a collection of leading edge research in Belief Revision. It contains the innovative ideas of respected and pioneering experts in the area, including Isaac Levi, Krister Segerberg, Sven Ove Hansson, Didier Dubois, and Henri Prade. The book addresses foundational issues of inductive reasoning and minimal change, generalizations of the standard belief revision theories, strategies for iterated revisions, probabilistic beliefs, multiagent environments and a variety of data structures and mechanisms for implementations. This book is suitable for students and researchers interested in knowledge representation and in the state of the art of the theory and practice of belief revision.

Full Product Details

Author:   M. Williams ,  Hans Rott
Publisher:   Springer
Imprint:   Springer
Edition:   2001 ed.
Volume:   22
Dimensions:   Width: 15.60cm , Height: 2.50cm , Length: 23.40cm
Weight:   1.830kg
ISBN:  

9780792370215

ISBN 10:   079237021
Pages:   454
Publication Date:   30 June 2001
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Invited Papers.- Inductive Expansion and Nonmonotonic Reasoning.- The Basic Dynamic Doxastic Logic of AGM.- Shielded Contraction.- A Computational Model for Belief Change and Fusing Ordered Belief Bases.- Contributed Papers.- An Operational Measure of Similarity Based on Change.- Toward a Formalization of Elaboration Tolerance: Adding and Deleting Axioms.- Assessing the Minimality of Change in Belief Revision: Capacities.- A Minimal Modelling for Successful Knowledge Base Revision.- Contraction of Epistemic States: A General Theory.- Two Notions of Epistemic Entrenchment.- Five Faces of Recovery.- Iterable AGM Functions.- Iterated Revision Operations Stemming from the History of an Agent’s Observations.- On a Full Meet Base Revision that Satisfies the Categorial Matching Principle.- Revision and Update Based on Stratified Forward Chaining.- Defeasible Inheritance and Reference Classes.- On Structured Belief Bases.- Iterated Syntax-based Revision in a Nonmonotonic Setting.- Revising and Updating Probabilistic Beliefs.- Bayesian Cognitive Diagnosis in Believable Multiagent Systems.- Revising Beliefs Received from Multiple Sources.

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