DocumentCode :
2032425
Title :
State-action pairs reduction for strong cyclic planning via state reachability
Author :
Wen, Zhong-Hua ; Chen, Hian-Lin ; Chang, Qing ; Hu, Yu-Long
Author_Institution :
Coll. of Inf. Eng., Xiangtan Univ., Xiangtan, China
Volume :
4
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1917
Lastpage :
1921
Abstract :
Strong cyclic planning under all state-action pairs has been addressed in the literature. Normally, the more the state-action pairs are, the higher of complexity is. In fact, there are many state-action pairs which are useless for strong cyclic planning. Before finding strong cyclic planning, it is significant to find a set of state-action pairs which are useless for strong cyclic planning, and to best of our knowledge, it is still an open problem. In this paper, hypergraph is defined for a nondeterministic state-transition system, adjacency matrix and reachability matrix of the hypergraph are defined. A method about how to use the adjancey matrix to count the reachability matrix is designed, and a way about how to use the reachability matrix to count the state reachability is presented in a nondeterministic state-transition system. Some important conclusions about strong cyclic planning are obtained by using the state reachability. These conclusions tell us what state-action pairs are useless when we search strong cyclic planning. So a lot of state-action pairs can be eliminated directly from all state-action pairs before searching strong cyclic planning. Our first contribution is the method which finds state reachability in nondeterministic state-transition system. A second contribution is the some important conclusions about strong cyclic planning, these works are significant to improve the efficiency of algorithm for solving strong cyclic planning.
Keywords :
matrix algebra; planning (artificial intelligence); reachability analysis; adjacency matrix; hypergraph; nondeterministic state-transition system; reachability matrix; state reachability; state-action pairs reduction; strong cyclic planning; Algorithm design and analysis; Artificial intelligence; Complexity theory; Finite element methods; Joints; Planning; USA Councils; hypergraph; nondeterministic state-transition system; state reachability; strong cyclic planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
Type :
conf
DOI :
10.1109/FSKD.2010.5569458
Filename :
5569458
Link To Document :
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