Expressiveness and tractability in knowledge representation and reasoning1
作者:
Hector J. Levesque,
Ronald J. Brachman,
期刊:
Computational Intelligence
(WILEY Available online 1987)
卷期:
Volume 3,
issue 1
页码: 78-93
ISSN:0824-7935
年代: 1987
DOI:10.1111/j.1467-8640.1987.tb00176.x
出版商: Blackwell Publishing Ltd
关键词: knowledge representation;description subsumption;complexity of reasoning;first‐order logic;frames;semantic networks;databases;représentation de connaissances;complexité;du raisonnement;logique du premier ordre;schémas;réseaux sémantiques;bases de données
数据来源: WILEY
摘要:
A fundamental computational limit on automated reasoning and its effect on knowledge representation is examined. Basically, the problem is that it can be more difficult to reason correctly with one representational language than with another and, moreover, that this difficulty increases dramatically as the expressive power of the language increases. This leads to a tradeoff between the expressiveness of a representational language and its computational tractability. Here we show that this tradeoff can be seen to underlie the differences among a number of existing representational formalisms, in addition to motivating many of the current research issues in knowledge representation.
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