Model-Based Reinforcement Learning: Theory and Practice 譯文

時間 2020-12-30

標籤強化學習-最前沿简体版

原文原文鏈接

目錄 Model-Based Reinforcement Learning: Theory and Practice Model-based techniques **Analytic gradient computation** **Sampling-based planning** **Model-based data generation** **Value-equivalence pred

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1. CONSENSUS:BRIDGING THEORY AND PRACTICE(第5章)
2. CONSENSUS:BRIDGING THEORY AND PRACTICE(第6章)
3. SIFT: Theory and Practice - Finding keypoints（轉）
4. SIFT: Theory and Practice - Introduction (轉)
5. SIFT: Theory and Practice - Keypoint orientations（轉）
6. Reinforcement learning and Deep learning
7. practice&theory
8. Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
9. CONSENSUS:BRIDGING THEORY AND PRACTICE(第0~3章)
10. Reinforcement Learning, Fast and Slow
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1. CONSENSUS:BRIDGING THEORY AND PRACTICE(第5章)
2. CONSENSUS:BRIDGING THEORY AND PRACTICE(第6章)
3. SIFT: Theory and Practice - Finding keypoints（轉）
4. SIFT: Theory and Practice - Introduction (轉)
5. SIFT: Theory and Practice - Keypoint orientations（轉）
6. Reinforcement learning and Deep learning
7. practice&theory
8. Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
9. CONSENSUS:BRIDGING THEORY AND PRACTICE(第0~3章)
10. Reinforcement Learning, Fast and Slow

>>更多相關文章<<