Frontiers in Belief Revision

Frontiers in Belief Revision

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Description

Frontiers in Belief Revision is a unique collection of leading edge research in Belief Revision. It contains the latest innovative ideas of highly 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.
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Product details

  • Hardback | 454 pages
  • 156 x 234 x 25.4mm | 1,830g
  • Dordrecht, Netherlands
  • English
  • 2001 ed.
  • VII, 454 p.
  • 079237021X
  • 9780792370215

Table of contents

Introduction; H. Rott, M.-A. Williams. Invited Papers. Inductive Expansion and Nonmonotonic Reasoning; I. Levi. The Basic Dynamic Doxastic Logic of AGM; K. Segerberg. Shielded Contraction; E. Ferme, S.O. Hansson. A Computational Model for Belief and Change and Fusing Ordered Belief Bases; S. Benferhat, et al. Contributed Papers. Minimal Change. An Operational Measure of Similarity Based on Change; M.-A. Williams. Toward a Formalization of Elaboration Tolerance: Adding and Deleting Axioms; E. Amir. Assessing the Minimality of Change in Belief Revision: Capacities; A. Sims, B. Sims. A Minimal Modelling for Successful Knowledge Base Revision; J. Delgrande. Theory: Generalizations and Iterations. Contraction of Epistemic States: A General Theory; A. Bochman. Two Notions of Epistemic Entrenchment; J. Cantwell. Five Faces of Recovery; E. Ferme. Iterable AGM Functions; C. Areces, V. Becher. Iterated Revision Operations Stemming from the History of an Agent's Observations; O. Papini. Structures for Implementations: Layers, Compartments, Inheritance Networks. On a Full Meet Base Revision that Satisfies the Categorial Matching Principle; M. Freund. Revision and Update Based on Stratified Forward Chaining; E.H. Bezzazi. Defeasible Inheritance and Reference Classes; L. Audibert, K. Schlechta. On Structured Belief Bases; R. Wassermann. Iterated Syntax-based Belief Revision in a Nonmonotonic Setting; B. Bessant, et al. Iterated Syntax-based Belief Revision in a Nonmonotonic Setting; B. Bessant, et al. Probability and Multiplicity. Revising and Updating Probabilistic Beliefs; G. Kern-Isberner. BayesianCognitive Diagnosis in Believable Multiagent Systems; F. de Rosis, et al. Revising Beliefs Received from Multiple Sources; A.F. Dragoni, P. Giorgini. Index.
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