Artificial Intelligence Series
275 pp., 7 x 9 in,
- Published: March 12, 1997
- Publisher: The MIT Press
Nonmonotonic reasoning provides formal methods that enable intelligent systems to operate adequately when faced with incomplete or changing information. In particular, it provides rigorous mechanisms for taking back conclusions that, in the presence of new information, turn out to be wrong and for deriving new, alternative conclusions instead. Nonmonotonic reasoning methods provide rigor similar to that of classical reasoning; they form a base for validation and verification and therefore increase confidence in intelligent systems that work with incomplete and changing information. Following a brief introduction to the concepts of predicate logic that are needed in the subsequent chapters, this book presents an in depth treatment of default logic. Other subjects covered include the major approaches of autoepistemic logic and circumscription, belief revision and its relationship to nonmonotonic inference, and briefly, the stable and well-founded semantics of logic programs.
This book offers a very elegant introduction to nonmonotonic reasoning. It covers the basics of all major nonmonotonic logistics and provides an extensive treatment of one of them—- default logic. The methodology of the operational semantics used for the discussion of default logic is very effective and makes this difficult material accessible to every student of logic. Problems appearing at the end of each chapter are well selected and provide additional opportunities for self-study.
Mirek Truszczynski, Department of Computer Science, University of Kentucky
This book provides an in-depth treatment of classical nonmonotonicsystems, in particular Default Logic. But its salient feature is adescription of exciting recent results on Inference Relations, BeliefRevision and their relations.
Daniel Lehmann, Professor of Computer Science, Hebrew University