Reinforcement learning: integrating learning and planning, exploitation and exploration
介紹 基於模型的RL 整體框架 基於仿真的搜索 Exploration and Exploitation 介紹 越看到後面，我越發覺得RL更像是一種思想，Policy，State都需要自己進行定義，計算value function的過程也有公式，但是不如深度學習那麼直接。 之前的章節是說到如何從經驗中得到policy和value function，這一節是如何從經驗中獲取模型。然後使用模型加經驗來
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相關文章
- 1. Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
- 2. Planning and Learning
- 3. Reinforcement learning and Deep learning
- 4. 《reinforcement learning：an introduction》第八章《Planning and Learning with Tabular Methods》總結
- 5. 8 Planning and Learning with Tabular Methods
- 6. Reinforcement Learning Note: Concept and MDP
- 7. Reinforcement Learning, Fast and Slow
- 8. 深度增強學習David Silver（八）——Integrating Learning and Planning
- 9. 【轉載】David Silver公開課8——Integrating Learning and Planning
- 10. Reinforcement Learning: Planning by DP