Specification morphisms for nonmonotonic knowledge systems

C. K. Macnish, Grigoris Antoniou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Conservative extensions of (classical) logical theories play an important role in software engineering, because they provide a formal basis for program refinement and guarantee the integrity and transparency of modules and objects. Similarly specification morphisms play a central role for information hiding and combining modules. Surprisingly, while the use of nonmonotonic theories for describing knowledge systems which may contain incomplete or uncertain data has been advocated for some time now, the above concepts have yet to be applied in this area. The aim of this work is to develop and apply analogues of these concepts in a nonmonotonic context. This paper builds on previous results, which focus on conservative extensions, extending the ideas to the more general case of specification morphisms.

Original languageEnglish
Title of host publicationAdvanced Topics in Artificial Intelligence - 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Proceedings
EditorsAbdul Sattar
PublisherSpringer Verlag
Pages246-254
Number of pages9
ISBN (Print)3540637974, 9783540637974
DOIs
Publication statusPublished - 1997
Externally publishedYes
Event10th Australian Joint Conference on Artificial Intelligence - Perth, Australia
Duration: 30 Nov 19974 Dec 1997
Conference number: 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1342
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Australian Joint Conference on Artificial Intelligence
Abbreviated titleAI 1997
CountryAustralia
CityPerth
Period30/11/974/12/97

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Macnish, C. K., & Antoniou, G. (1997). Specification morphisms for nonmonotonic knowledge systems. In A. Sattar (Ed.), Advanced Topics in Artificial Intelligence - 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Proceedings (pp. 246-254). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1342). Springer Verlag. https://doi.org/10.1007/3-540-63797-4_77