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Handling inconsistency in knowledge systems

Handling inconsistency in knowledge systems PART 1 Introduction Handling inconsistency in knowledge systems Knowledge systems and logic Knowledge representation and reasoning systems, or shorter: knowledge sys­ tems, are based on two fundamental operations : 1. New incoming pieces of information must be assimilated into the knowl­ edge base by means of an appropriate update operation. This includes simple insertion of new information, deletion (retraction) of old infor­ mation, and possibly a number of more involved change procedures for assimilating new pieces of information which are in conflict with some already-stored pieces. The update operation should satisfy some principle of minimal change or minimal mutilation as proposed, e.g., in [BEL 77]. 2. Queries posed to the knowledge base must be answered by means of a query answering, or inference, operation. The inference operation should be complete with respect to some well-understood logic (restricted to con­ sistent premise sets), and sound with respect to a preferential entailment relation in that logic. The relationship to logic is only obvious for the latter operation: while in a logical system theorems are proved from (or entailed by) a theory on the ba­ sis of the underlying consequence relation, queries in a knowledge system are answered on the basis of http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Non-Classical Logics Taylor & Francis

Handling inconsistency in knowledge systems

Wagner, Gerd
Journal of Applied Non-Classical Logics , Volume 7 (1-2): 6 – Jan 1, 1997
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Handling inconsistency in knowledge systems

Abstract

PART 1 Introduction Handling inconsistency in knowledge systems Knowledge systems and logic Knowledge representation and reasoning systems, or shorter: knowledge sys­ tems, are based on two fundamental operations : 1. New incoming pieces of information must be assimilated into the knowl­ edge base by means of an appropriate update operation. This includes simple insertion of new information, deletion (retraction) of old infor­ mation, and possibly a number of more involved change...
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Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1958-5780
eISSN
1166-3081
DOI
10.1080/11663081.1997.10510898
Publisher site
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Abstract

PART 1 Introduction Handling inconsistency in knowledge systems Knowledge systems and logic Knowledge representation and reasoning systems, or shorter: knowledge sys­ tems, are based on two fundamental operations : 1. New incoming pieces of information must be assimilated into the knowl­ edge base by means of an appropriate update operation. This includes simple insertion of new information, deletion (retraction) of old infor­ mation, and possibly a number of more involved change procedures for assimilating new pieces of information which are in conflict with some already-stored pieces. The update operation should satisfy some principle of minimal change or minimal mutilation as proposed, e.g., in [BEL 77]. 2. Queries posed to the knowledge base must be answered by means of a query answering, or inference, operation. The inference operation should be complete with respect to some well-understood logic (restricted to con­ sistent premise sets), and sound with respect to a preferential entailment relation in that logic. The relationship to logic is only obvious for the latter operation: while in a logical system theorems are proved from (or entailed by) a theory on the ba­ sis of the underlying consequence relation, queries in a knowledge system are answered on the basis of

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Journal of Applied Non-Classical Logics – Taylor & Francis

Published: Jan 1, 1997

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