DocumentCode :
441712
Title :
Most required goals for extracting heuristics in planning
Author :
Cai, Dun-Bo ; Gu, Wen-Xinag
Author_Institution :
Sch. of Comput., Northeast Normal Univ., Changchun, China
Volume :
2
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
1132
Abstract :
A novel heuristic search planner, MRGFF (most required goals for fast forward planning), is advanced in this paper based on the well-known fast-forward planning system, MRGFF uses a notion, most required goals, to compute a lower heuristic estimate of a state and to prune the search space efficiently. The system has been implemented in C on a machine with a Pentium III processor at 600MHz and 160M memory, running Linux. Empirical results show the excellent performance achieved by our algorithm in terms of efficiency, scalability and accuracy.
Keywords :
heuristic programming; planning (artificial intelligence); search problems; fast-forward planning system; heuristic search planner; most required goal; Application specific processors; Computer aided instruction; Electronic mail; Linux; Machine learning; Power system planning; Runtime; Scalability; State estimation; Strips; Most Required Goals; Planning; estimation; heuristic search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527113
Filename :
1527113
Link To Document :
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