Title :
Combining heuristics for default logic reasoning systems
Author :
Nicolas, Pascal ; Saubion, Frédéric ; Stéphan, Igor
Author_Institution :
LERIA, Angers Univ., France
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
Keywords :
artificial intelligence; computational complexity; genetic algorithms; knowledge representation; nonmonotonic reasoning; automated default reasoning system; default logic reasoning systems; expressive power; genetic algorithms; heuristics; knowledge representation; local search techniques; nonmonotonic reasoning; theoretical complexity; Artificial intelligence; Calculus; Evolutionary computation; Genetic algorithms; Knowledge representation; Logic; Modems; Simulated annealing; Space exploration; Transportation;
Conference_Titel :
Tools with Artificial Intelligence, 2000. ICTAI 2000. Proceedings. 12th IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7695-0909-6
DOI :
10.1109/TAI.2000.889899