David Silver《Reinforcement Learning》课程解读—— Lecture 4： Model-Free Prediction

时间 2020-08-03

标签 david silver reinforcement learning 课程解读 lecture model free prediction 繁體版

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David Silver《Reinforcement Learning》课程解读—— Lecture 4： Model-Free Prediction DP动态规划可以解决已知environment的MDP问题，即已知 S,A,P,R,γ ，根据是否已知policy又将问题划分为prediction和control的问题。本质上来讲这种known MDP问题已知environment即转移矩阵与

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1. David Silver《Reinforcement Learning》课程解读—— Lecture 4： Model-Free Prediction
2. David Silver《Reinforcement Learning》课程解读—— Lecture 1： Introduction to Reinforcement Learning
3. David Silver《Reinforcement Learning》课程解读—— Lecture 5： Model-Free Control
4. David Silver《Reinforcement Learning》课程解读—— Lecture 3： Planning by Dynamic Programming
5. Reinforcement Learning_By David Silver笔记四: Model Free Prediction
6. UCL Course on RL by David Silver Lecture 1: Introduction to Reinforcement Learning
7. silver课程笔记----Lecture 1: Introduction to Reinforcement Learning
8. 【转载】David Silver公开课4——Model-Free Learning
9. Reinforcement Learning_By David Silver笔记五: Model Free Control
10. [Reinforcement Learning] Model-Free Prediction
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1. David Silver《Reinforcement Learning》课程解读—— Lecture 4： Model-Free Prediction
2. David Silver《Reinforcement Learning》课程解读—— Lecture 1： Introduction to Reinforcement Learning
3. David Silver《Reinforcement Learning》课程解读—— Lecture 5： Model-Free Control
4. David Silver《Reinforcement Learning》课程解读—— Lecture 3： Planning by Dynamic Programming
5. Reinforcement Learning_By David Silver笔记四: Model Free Prediction
6. UCL Course on RL by David Silver Lecture 1: Introduction to Reinforcement Learning
7. silver课程笔记----Lecture 1: Introduction to Reinforcement Learning
8. 【转载】David Silver公开课4——Model-Free Learning
9. Reinforcement Learning_By David Silver笔记五: Model Free Control
10. [Reinforcement Learning] Model-Free Prediction

>>更多相关文章<<