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Preface |
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Contributors |
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Acknowledgements |
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Mathematical Notation |
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Acronyms |
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Introduction |
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Part 1: Foundamentals |
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Chapter 1: Introduction to Deep Learning |
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Chapter 2: Introduction to Reinforcement Learning |
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Chapter 3: Taxonomy of Reinforcement Learning Algorithms |
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Chapter 4: Deep Q-Networks |
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Chapter 5: Policy Gradient |
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Chapter 6: Combine Deep Q-Networks with Actor-Critic |
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Part II: Research |
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Chapter 7: Challenges of Reinforcement Learning |
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Chapter 8: Imitation Learning |
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Chapter 9: Integrating Learning and Planning |
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Chapter 10: Hierarchical Reinforcement Learning |
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Chapter 11: Multi-Agent Reinforcement Learning |
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Chapter 12: Parallel Computing |
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Part III: Applications |
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Chapter 13: Learning to Run |
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Chapter 14: Robust Image Enhancement |
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Chapter 15: AlphaZero |
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Chapter 16: Robot Learning in Simulation |
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Chapter 17: Arena Platform for Multi-Agent Reinforcement Learning |
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Chapter 18: Tricks of Implementation |
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Part IV: Summary |
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Chapter 19: Algorithm Table |
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Chapter 20: Algorithm Cheatsheet |
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