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a05_rl icon a05_rl

本课程主要介绍强化学习的基础知识，其目标是帮助同学们快速、顺利地进入强化学习及其应用领域的研究工作。课程主要内容包含有限马尔可夫决策过程，动态规划，无模型预测与控制(SASA,Q-Learning)，价值函数逼近(DQN)，策略梯度方法(REINFORCE)，执行者/评论者方法（AC,TRPO,PPO)，连续动作空间的确定性策略(DDPG)。

cv-xueba.github.io icon cv-xueba.github.io

这里是鲁鹏老师团队的官方小站 (CV学吧）的根据地，欢迎！This is the official station of CV-xueba. Welcome ! ^_^

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Intro to Reinforcement Learning (强化学习纲要）

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