Conditionals, Information, and Inference - International Workshop, WCII 2002, Hagen, Germany, May 13-15, 2002, Revised Selected Papers (Paperback, 2005 ed.)

Conditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, physical laws, and social norms. On the other hand, as default rules or general implications, they constitute a basic tool for reasoning, even in the presence of uncertainty. In this sense, conditionals are intimately connected both to information and inference. Due to their non-Boolean nature, however, conditionals are not easily dealt with. They are not simply true or false - rather, a conditional "if A then B" provides a context, A, for B to be plausible (or true) and must not be confused with "A entails B" or with the material implication "not A or B." This ill- trates how conditionals represent information, understood in its strict sense as reduction of uncertainty. To learn that, in the context A, the proposition B is plausible, may reduce uncertainty about B and hence is information. The ab- ity to predict such conditioned propositions is knowledge and as such (earlier) acquired information. The ?rst work on conditional objects dates back to Boole in the 19th c- tury, and the interest in conditionals was revived in the second half of the 20th century, when the emerging Arti?cial Intelligence made claims for appropriate formaltoolstohandle"generalizedrules."Sincethen,conditionalshavebeenthe topic of countless publications, each emphasizing their relevance for knowledge representation, plausible reasoning, nonmonotonic inference, and belief revision.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Lecture Notes in Artificial Intelligence, 3301
Release date:	May 2005
First published:	2005
Editors:	Gabriele Kern-Isberner • Wilhelm Roedder • Friedhelm Kulmann
Dimensions:	235 x 155 x 12mm (L x W x T)
Format:	Paperback
Pages:	219
Edition:	2005 ed.
ISBN-13:	978-3-540-25332-7
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-540-25332-7
Barcode:	9783540253327

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