Solving stochastic path problem: Particle swarm optimization approach

被引：0

作者：

Momtazi, Saeedeh ^{[1
]}

Kafi, Somayeh ^{[1
]}

Beigy, Hamid ^{[1
]}

机构：

[1] Sharif Univ Technol, Dept Comp Engn, Tehran, Iran

来源：

NEW FRONTIERS IN APPLIED ARTIFICIAL INTELLIGENCE | 2008年 / 5027卷

关键词：

Particle Swarm Optimization; Stochastic Shortest Path Problem; swarm intelligence;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An stochastic version of the classical shortest path problem whereby for each node of a graph, a probability distribution over the set of successor nodes must be chosen so as to reach a certain destination node with minimum expected cost. In this paper, we propose a new algorithm based on Particle Swarm Optimization (PSO) for solving Stochastic Shortest Path Problem (SSPP). The comparison of our algorithm with other algorithms indicates that its performance is suitable even by the less number of iterations.

引用

页码：590 / 600

页数：11

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