Reinforcement Learning - Charles Isbell from Georgia Tech
你可以從這裏 Udacity上的課程 聽課，是比較簡單易懂的教程，比起單純看Sutton的書還更有意思更加無痛入門一點 （Sutton的書寫的是很詳細不過真的看的很累，可以結合着看吧） Markov Decision Processes Markov property means only the present matters. The rules are stationary. Feature
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相關文章
- 1. Deep Reinforcement Learning: Pong from Pixels
- 2. (轉) Deep Reinforcement Learning: Pong from Pixels
- 3. Reinforcement Learning for Relation Classification from Noisy Data
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- 10. Reinforcement learning and Deep learning