Contemporary theories of reinforcement learning are rooted in the dopaminergic reward system.

当代的强化学习理论是基于多巴胺奖赏系统。

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Due to the theoretical limitation that it assumes that an environment is Markovian, traditional reinforcement learning algorithms cannot be applied directly to multi-agent system.

由于强化学习理论的限制，在多智能体系统中马尔科夫过程模型不再适用，因此不能把强化学习直接用于多智能体的协作学习问题。

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For vector control AC drive system, the thesis presented a fuzzy neural network speed controller based on reinforcement learning.

针对矢量控制交流调速系统，该文提出并设计了一种基于再励学习的模糊神经网络速度控制器。

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