This thesis proposed Vector Base Learning (VBL) algorithm.

提出了矢量基学习算法。

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A fuzzy Q learning algorithm is proposed in this dissertation, which map continuous state Spaces to continuous action Spaces by fuzzy inference system and then learn a rule base.

首先，提出一种模糊Q学习算法，通过模糊推理系统将连续的状态空间映射到连续的动作空间，然后通过学习得到一个完整的规则库。

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This hierarchical learning algorithm can reduce the redundant rules and simplify the fuzzy rule base.

这种二层优化方法能较好地减少模糊规则基的冗余度，化简模糊规则基。

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