Forgetting for defeasible logic

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Author(s)
Antoniou, Grigoris
Eiter, Thomas
Wang, Kewen
Year published
2012
Metadata
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The concept of forgetting has received significant interest in artificial intelligence recently. Informally, given a knowledge base, we may wish to forget about (or discard) some redundant parts (such as atoms, predicates, concepts, etc) but still preserve the consequences for certain forms of reasoning. In nonmonotonic reasoning, so far forgetting has been studied only in the context of extension based approaches, mainly answer-set programming. In this paper forgetting is studied in the context of defeasible logic, which is a simple, efficient and sceptical nonmonotonic reasoning approach.The concept of forgetting has received significant interest in artificial intelligence recently. Informally, given a knowledge base, we may wish to forget about (or discard) some redundant parts (such as atoms, predicates, concepts, etc) but still preserve the consequences for certain forms of reasoning. In nonmonotonic reasoning, so far forgetting has been studied only in the context of extension based approaches, mainly answer-set programming. In this paper forgetting is studied in the context of defeasible logic, which is a simple, efficient and sceptical nonmonotonic reasoning approach.
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Conference Title
LOGIC FOR PROGRAMMING, ARTIFICIAL INTELLIGENCE, AND REASONING (LPAR-18)
Volume
7180
Copyright Statement
© 2012 Springer. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher.The original publication is available at www.springerlink.com
Subject
Artificial Intelligence and Image Processing not elsewhere classified