In this paper, we propose a fuzzy reinforcement algorithm, which map continuous state Spaces to continuous action Spaces by fuzzy inference system and then learn a rule base.
论文提出一种模糊强化学习算法，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。
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。
A novel hybrid neural fuzzy inference system is presented. Only based on the desired input output data pairs, are the knowledge acquisition and initial fuzzy rule sets available.
设计一种新型混合模糊神经推理系统，该系统仅从期望输入输出数据集即可达到获取知识、确定模糊初始规则基的目的。
When the knowledge rule is found in the knowledge files, T-S fuzzy inference model is applied to resolution of question.
当在知识库中搜索到相应的知识规则后，采用T - s模糊推理模型的求解策略进行求解。
Decision inference of the extended decision rules was implemented using fuzzy CRI (compositional rule of inference).
用关系合成的模糊推理方法，实现了扩展决策规则集的决策推理。
While the article proposes the improved inference and self-learning method of fuzzy rule.
并提出了模糊规则的改进推理和自学习方法。
Based on the analysis of the mechanism of fuzzy reasoning by compositional rule of inference, the principle of how to achieve the same results with interpolation method is presented.
在对采用合成推理规则进行模糊推理的机制进行分析的基础上，给出了利用插值法也可以得到相同结果的原理。
Based on the analysis of the mechanism of fuzzy reasoning by compositional rule of inference, the principle of how to achieve the same results with interpolation method is presented.
在对采用合成推理规则进行模糊推理的机制进行分析的基础上，给出了利用插值法也可以得到相同结果的原理。
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