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Nonmonotonic reasoning, preferential models and cumulative logics

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Kraus, Sarit, Lehmann, Daniel, Magidor, Menachem·1990·Artificial Intelligence

Abstract

Abstract Many systems that exhibit nonmonotonic behavior have been described and studied already in the literature. The general notion of nonmonotonic reasoning, though, has almost always been described only negatively, by the property it does not enjoy, i.e. monotonicity. We study here general patterns of nonmonotonic reasoning and try to isolate properties that could help us map the field of nonmonotonic reasoning by reference to positive properties. We concentrate on a number of families of nonmonotonic consequence relations, defined in the style of Gentzen [13]. Both proof-theoretic and semantic points of view are developed in parallel. The former point of view was pioneered by Gabbay [10], while the latter has been advocated by Shoham [38]. Five such families are defined and characterized by representation theorems, relating the two points of view. One of the families of interest, that of preferential relations, turns out to have been studied by Adams [2]. The preferential models proposed here are a much stronger tool than Adams' probabilistic semantics. The basic language used in this paper is that of propositional logic. The extension of our results to first-order predicate calculi and the study of the computational complexity of the decision problems described in this paper will be treated in another paper.

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Metadata

Authors
Kraus, S., Lehmann, D., & Magidor, M.
Venue
Artificial Intelligence
Publisher
Elsevier BV
Published
1990-07
Volume
44
Issue
1-2
Pages
167-207
ISSN
0004-3702 (ISSN-L)
OpenAlex
W2080142817
Cited by
1,660
References
1
FWCI
26.11
Type
journal article
Language
en
Open access
green

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Kraus, S., Lehmann, D., & Magidor, M. (1990). Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence. https://doi.org/10.1016/0004-3702(90)90101-5

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