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A Hierarchical Reinforcement Learning Algorithm Based on Fuzzy Clustering
A new algorithm for the automatic generation of the Option Hierarchical Reinforcement Learning is presented. The algorithm takes the state space detected by the agent as input in the initial learning phase,and clusters the states by employing fuzzy clustering. Based on the clustered state sets, the intrastrategies are learned by an experience replay procedure. As a result, the options are generated. The validity of the algorithm is demonstrated by simulation experiments.
ZHANG Xin , DAI Shuai . A Hierarchical Reinforcement Learning Algorithm Based on Fuzzy Clustering[J]. Computer Engineering & Science, 2010 , 32(1) : 55 -56 . DOI: 10.3969/j.issn.1007130X.2010.
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