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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This characteristic of reinforcement learning must increase learning difficulty for intelligent system and learning time also grows up.

强化学习的这种特性必然增加智能系统的困难性，学习时间增长。

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