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。
MAXQ, a hierarchical reinforcement learning method for multi-agent system, is proposed in recent years.
MAXQ分层多智能体学习方法是近年来被提出的一种新方法。
Multi-Agent technology achieves the personalized in ITS, and reinforcement learning algorithm makes teaching strategies with the intelligent.
多代理体技术实现了教学的个性化，强化学习算法使得教学策略具有智能化。
Tis paper presents two-layer reinforcement learning method for multi-agent cooperation.
提出了多智能体协作的两层强化学习方法。
Tis paper presents two-layer reinforcement learning method for multi-agent cooperation.
提出了多智能体协作的两层强化学习方法。
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