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Published Articles >> Table of Contents >> Abstract
12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00)
p. 0393
Combining heuristics for default logic reasoning systems
P. Nicolas, LERIA, Angers Univ., France
F. Saubion, LERIA, Angers Univ., France
I. Stephan, LERIA, Angers Univ., France
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889899
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Abstract: In Artificial Intelligence, Default Logic is recognized as a powerful framework for knowledge representation when one has to deal with incomplete information. Its expressive power is suitable for nonmonotonic reasoning, but the counterpart is its very high level of theoretical complexity. Today, some operational systems are able to deal with real world applications. However finding a default logic extension in a practical way is not yet possible in whole generality. This paper shows how modern heuristics such as genetic algorithms and local search techniques can be used and combined to build an automated default reasoning system. We give a general description of the required basic components and we exhibit experimental results.
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 Additional Information
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Index Terms- knowledge representation; nonmonotonic reasoning; genetic algorithms; computational complexity; artificial intelligence; heuristics; default logic reasoning systems; knowledge representation; expressive power; nonmonotonic reasoning; theoretical complexity; genetic algorithms; local search techniques; automated default reasoning system
Citation:
P. Nicolas, F. Saubion, I. Stephan,
"Combining heuristics for default logic reasoning systems,"
ictai,
p. 0393,
12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00),
2000
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