Computer Science ›› 2015, Vol. 42 ›› Issue (4): 217-220, 257.doi: 10.11896/j.issn.1002-137X.2015.04.044

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Solving Strong Cyclic Planning with Minimal Expectation Weight

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

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

Abstract: In real world,the action’s execution often takes a cost.Due to the interference of the external environment,the result of an action’s execution is uncertain.To solve this problem,we added weight to the action in system,used a probability distribution to show the stochastic state transition.A method of solving strong cyclic planning with minimal expectation weight was designed based on the proposed concept of expectation weight for strong cyclic planning.Mainly,this method applies depth-first search for getting all strong cyclic plannings.Then,it uses Gaussian elimination to slove the problem after converting the plannings into linear equations with variables in expectation weight.

Key words: Uncertainty planning,Probability distribution,Strong cyclic planning with minimal expectation weight,Depth-first search,Gaussian elimination

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