求解随机最短路径马尔可夫决策过程的组合加速程序

2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering Pub Date : 2010-11-01 DOI:10.1109/ISKE.2010.5680801

M. G. García-Hernández, J. Ruiz-Pinales, S. Ledesma-Orozco, J. Aviña-Cervantes, E. Onaindía, A. Reyes-Ballesteros

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引用次数: 2

摘要

针对随机最短路径马尔可夫决策过程的求解问题，提出了一种结合加速变量迭代和改进优先扫描的方法。为了获得最快的解决方案，我们测试了异步更新、优先级划分和优先级清理。并将拓扑排序算法与静态排序算法进行了比较。给出了有限状态和动作空间随机最短路径问题的实验结果。

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Combination of acceleration procedures for solving stochastic shortest-path Markov decision processes

In this paper we propose the combination of accelerated variants of value iteration with improved prioritized sweeping for the solution of stochastic shortest path Markov decision processes. For the fastest solution, asynchronous updates, prioritization and prioritized sweeping have been tested. A topological reordering algorithm was also compared with a static reordering algorithm. Experimental results obtained on afinite state and action-space stochastic shortest path problem are presented.

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2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering

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