DocumentCode :
1935330
Title :
A New Method for Parallel Planning via Heuristic Search
Author :
Gu, Wen-xiang ; Wen, Li-hong
Author_Institution :
NorthEast Normal Univ., Jilin
Volume :
6
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
3128
Lastpage :
3132
Abstract :
Due to the need of solving the problem of exponential branching factor, parallel planning through heuristic state space search is a challenging problem. A new method based on heuristic state search is introduced. The method generates parallel plan by parallelism of one action (center action) and other independent actions applicable in one state, thereby, avoids the problem mentioned above. Furthermore, the method considers the negative interaction between actions and uses two time-step partial plan that adds more goals to be substitute of one action during the process of choosing the center action. PPFF (parallel planning FF) is designed based on FF (Fast-forward) planning system and the method introduced above. Primary analysis indicates that the running time of PPFF is faster than existing parallel planning systems.
Keywords :
artificial intelligence; search problems; exponential branching factor; fast-forward planning system; heuristic state search; intelligence planning; parallel planning; Computer science; Cybernetics; Data mining; Educational institutions; Intelligent robots; Machine learning; Machine learning algorithms; Parallel processing; Process planning; State-space methods; Center action; Exponential branching factor; Heuristic state space search; Independent actions; Intelligence planning; Parallel plans;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370685
Filename :
4370685
Link To Document :
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