| 有限规划水平自适应Markov决策过程的参数决策 |
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| 引用本文： | 李江洪,韩正之. 有限规划水平自适应Markov决策过程的参数决策[J]. 应用科学学报, 2000, 18(4): 335-339 |
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| 作者姓名： | 李江洪 韩正之 |
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| 作者单位： | 上海交通大学智能工程研究所, 上海 200030 |
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| 基金项目： | 国家自然科学基金资助项目!（69874025） |
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| 摘 要： | 针对现有Markov决策过程自适应决策方法仅研究无限规划水平自适应决策的不足,提出了一种有限规划水平Markov决策过程自适应决策算法.算法的基本思想是运用Bayes理论对未知系统进行"学习",并且在每次决策时以最大概率保证实际决策为最优决策.最后用仿真结果表明了算法的有效性.
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| 关 键 词： | Markov决策过程 自适应决策 Bayes原理 |
| 收稿时间： | 1999-11-17 |
| 修稿时间： | 2000-01-17 |
Parameter Decision Making in Adaptive Markov Decision Process with Finite Planning Horizon |
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| LI Jiang-hong,HAN Zheng-zhi. Parameter Decision Making in Adaptive Markov Decision Process with Finite Planning Horizon[J]. Journal of Applied Sciences, 2000, 18(4): 335-339 |
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| Authors: | LI Jiang-hong HAN Zheng-zhi |
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| Affiliation: | Institute of Intelligence Engineering, Shanghai Jiaotong University, Shanghai 200030, China |
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| Abstract: | An algorithm is proposed for adaptive MDP with finite planning horizon by reason of the fact that all current algorithms only consider adaptive MDP with infinite planning horizon. Bayes principle is applied to learn an unknown system; and for every decision the probability that the actual decision equals the optimal decision is maximized. Simulation results demonstrate the validity of the new algorithm. |
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| Keywords: | Markov decision process (MDP) adaptive decision making Bayes principle |
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