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A Two-Level Hierarchical Markov Decision Model with Considering Interaction between Levels

A Two-Level Hierarchical Markov Decision Model with Considering Interaction between Levels
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摘要 Decision in reality often have the characteristic of hierarchy because of the hierarchy of an organization's structure. In this paper, we propose a two-level hierarchic Markov decision model that considers the interactions of agents in different levels and different time scales of levels. A backward induction algo- rithm is given for the model to solve the optimal policy of finite stage hierarchic decision problem. The proposed model and its algorithm are illustrated with an example about two-level hierar- chical decision problem of infrastructure maintenance. The opti- mal policy of the example is solved and the impacts of interactions between levels on decision making are analyzed. Decision in reality often have the characteristic of hierarchy because of the hierarchy of an organization's structure. In this paper, we propose a two-level hierarchic Markov decision model that considers the interactions of agents in different levels and different time scales of levels. A backward induction algo- rithm is given for the model to solve the optimal policy of finite stage hierarchic decision problem. The proposed model and its algorithm are illustrated with an example about two-level hierar- chical decision problem of infrastructure maintenance. The opti- mal policy of the example is solved and the impacts of interactions between levels on decision making are analyzed.
出处 《Wuhan University Journal of Natural Sciences》 CAS 2013年第1期37-41,共5页 武汉大学学报(自然科学英文版)
基金 Supported by the National Natural Science Foundation of China (70971048)
关键词 two-level hierarchic Markov decision processes multi-time scale backward induction two-level hierarchic Markov decision processes multi-time scale backward induction
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