Deep Reinforcement Learning 基础知识（DQN方面 ）
解释的挺清楚的 Introduction 深度增强学习Deep Reinforcement Learning是将深度学习与增强学习结合起来从而实现从Perception感知到Action动作的端对端学习的一种全新的算法。简单的说，就是和人类一样，输入感知信息比如视觉，然后通过深度神经网络，直接输出动作，中间没有hand-crafted工作。深度增强学习具备使机器人实现完全自主的学习一种甚至多种技能
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相关文章
- 1. Deep Reinforcement Learning
- 2. 【强化学习】DQN(Deep reinforcement learning) Basic
- 3. Generating Text with Deep Reinforcement Learning
- 4. 零基础10分钟运行DQN图文教程 Playing Flappy Bird Using Deep Reinforcement Learning (Based on Deep Q Learning DQN
- 5. Relational Deep Reinforcement Learning
- 6. Reinforcement learning and Deep learning
- 7. Continuous control with Deep Reinforcement Learning
- 8. RL论文阅读【四】Deep Reinforcement Learning with Double Q-learning（Double DQN）
- 9. Deep Reinforcement Learning Variants ofMulti-Agent Learning Algorithms
- 10. Deep Reinforcement Learning for List-wise Recommendations