deep-reinforcement-learning
  • 介绍
  • 前言
    • 神经网络
    • 研究平台
      • 街机游戏
      • 竞速游戏
      • 第一人称射击游戏
      • 开放世界游戏
      • 即时战略游戏
      • 团队体育游戏
      • 文字冒险游戏
      • OpenAI Gym & Universe
  • 方法
    • 街机游戏
      • DQN
      • DRQN
      • Gorila
      • Double DQN
      • Prioritized Experience Replay
      • Dueling DQN
      • Bootstrapped DQN
      • Multiagent DQN
      • Progressive Neural Networks
      • A3C
      • Retrace(λ)
      • ACER
      • ACKTR
      • TRPO
      • PPO
      • UNREAL
      • IMPALA
      • Distributional DQN
      • Noisy-Net
      • Rainbow
      • ES
      • NS-ES
      • Deep GA
      • Playing Atari with Six Neurons
      • UCTtoClassification
      • Policy Distillation
      • Actor-Mimic
      • Action-Conditional Video Prediction
      • Self-Supervision
      • HRA
    • 蒙特祖玛的复仇
      • Hierarchical-DQN
      • DQN-CTS
      • Pixel Recurrent Neural Networks
      • DQN-PixelCNN
      • Ape-X
      • DQfD
      • Ape-X DQfD
      • Natural Language Guided Reinforcement Learning
    • 竞速游戏
      • Direct Perception
      • DDPG
      • TD3
    • 第一人称射击游戏
      • SLAM-Augmented DQN
      • Direct Future Prediction
      • For The Win
    • 开放世界游戏
      • H-DRLN
      • Feedback Recurrent Memory Q-Network
      • Teacher-Student Curriculum Learning
    • 即时战略游戏
      • Puppet Search
      • Combined Strategic and Tacticals
      • Zero Order
      • IQL
      • COMA
      • BiC-Net
      • Macro-action SL
      • Macro-action PPO
      • On Reinforcement Learning for Full-length Game of StarCraft
      • AlphaStar
    • 团队体育游戏
      • DDPG + Inverting Gradients
      • DDPG + Mixing policy targets
      • Object-centric prediction
    • 文字冒险游戏
      • LSTM-DQN
      • DRRN
      • Affordance Based Action Selection
      • Golovin
      • AE-DQN
    • 开放的挑战
      • 游戏通用性
      • 稀疏、延迟、欺骗性的回报
      • 多智能体
      • 终身适应
      • 像人类一样玩游戏
      • 可调节的性能等级
      • 处理巨大的状态空间
      • 工业界应用
      • 游戏开发的交互式工具
      • 创造新的游戏
      • 学习游戏的模型
      • 计算资源
  • 附录
    • Distributional RL
      • QR-DQN
    • Policy Gradient
      • Off-Policy Actor-Critic
      • Generalized Advantage Estimation
      • Soft Actor-Critic
      • PPO-Penalty
    • Model-Based RL
      • I2A
      • MBMF
      • MBVE
      • World Models
    • Imitation Learning and Inverse Reinforcement Learning
      • GAIL
    • Transfer and Multitask RL
      • HER
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  2. Model-Based RL

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Imagination-Augmented Agents for Deep Reinforcement Learning