Computer Science ›› 2015, Vol. 42 ›› Issue (2): 228-232.doi: 10.11896/j.issn.1002-137X.2015.02.047

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Solving Minimal Cost Strong Planning Solution by Hierarchical Algorithm

WU Xiao-hui, WEN Zhong-hua, LI Yang and LAO Jia-qi   

  • Online:2018-11-14 Published:2018-11-14

Abstract: In nondeterministic planning areas,previous studies on the strong planning solution focused on the solution itself,with little regard for the required cost of nondeterministic transfer system performing an action,and the algorithms’ efficiency which exists is not high.Aiming at this problem,we introduced a strong planning hierarchical method in model-checking,designed an algorithm to solve the minimal cost strong planning solution quickly.Firstly,this algorithm uses strong planning hierarchical method to get hierarchical states of nondeterministic problem,and then it reversely searches the minimal cost strong planning solution by using the hierarchical information.In the search process,according to the algorithm strategy,the upper and lower bounds of required searching layer are real-time updated to avoid a lot of useless search,improving search efficiency.Experimental results show that this algorithm can not only solve the minimal cost strong planning solution quickly and precisely,but also run more efficient than existing algorithms.And the greater the number of layers and the number of actions,the more obvious the advantages.

Key words: Nondeterministic planning,Minimal cost strong planning solution,Model-checking,Strong planning hierarchical method

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