awesome-reinforcement-learning
Learning Resources And Links Of Reinforcement Learning （updating）
https://github.com/tinyzqh/awesome-reinforcement-learning
Last synced: 5 days ago
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- David Silver's course
- Deep RL Bootcamp
- Play pong with deep reinforcement learning based on pixel
- REINFORCEMENT LEARNING AND OPTIMAL CONTROL
- CS234: Reinforcement Learning Winter 2019
- 强化学习知识大讲堂
- 南京大学俞扬博士万字演讲全文：强化学习前沿
- OpenAi Spinning Up
- An Introduction to Deep Reinforcement Learning
- Foundations and Trends® in Machine Learning
- 中文翻译-2018秋季CS294-112深度强化学习
- CS294课程中文笔记-1
- 作业讲解
- David视频里所使用的讲义pdf
- John Schulmann's lectures
- CS 287: Advanced Robotics, Fall 2015
- Deep Learning (DLSS) and Reinforcement Learning (RLSS) Summer School, Montreal 2017
- 强化学习教程(莫烦)
- Deep Learning in a Nutshell: Reinforcement Learning
- AlphaGo
- 加州大学伯克利分校机器人学专家 Sergey Levine
- 加拿大阿尔伯塔大学著名增强学习大师Richard S. Sutton 教授
- Google DeepMind AlphaGo项目的主程序员 David Silver 博士
- 机器博弈专家Tuomas Sandholm教授
- 强化学习系列教程
- 强化学习系列教程
- Hands-On Reinforcement Learning With Python
- Reinforcement Learning: Theory and Python Implementation
- Advanced Deep Learning and Reinforcement Learning
- David Silver《深度强化学习》公开课教程学习笔记以及实战
- 南京大学俞扬博士万字演讲全文：强化学习前沿
- David Silver《深度强化学习》公开课教程学习笔记以及实战
- David Silver's course
- Play pong with deep reinforcement learning based on pixel
- Deep Learning (DLSS) and Reinforcement Learning (RLSS) Summer School, Montreal 2017
- CS294课程中文笔记-2 (记录较好)
- REINFORCEMENT LEARNING AND OPTIMAL CONTROL
- Deep Learning in a Nutshell: Reinforcement Learning
- Google DeepMind AlphaGo项目的主程序员 David Silver 博士
- 机器博弈专家Tuomas Sandholm教授
- CS 294: Deep Reinforcement Learning
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论文
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Implementation of Algorithms
- SAC
- PPO
- TRPO
- C51 - Atom DQN): Bellemare et al, 2017
- Dueling DQN
- Double DQN
- I2A - Augmented Agents): Weber et al, 2017
- AlphaZero-arxiv - Play) :Silver et al, 2017
- World Models
- MBMF - Based RL with Model-Free Fine-Tuning): Nagabandi et al, 2017
- MBVE - Based Value Expansion): Feinberg et al, 2018
- PathNet
- SAC - Policy Maximum Entropy): Haarnoja et al, 2018
- Policy distillation
- A2C / A3C - Critic): Mnih et al, 2016
- DDPG
- Prioritized experience replay
- DPG
- HER
- DQN-arxiv - Networks ): Mnih et al, 2013
- DQN-nature - Network ); Mnih et al, 2015
- QR-DQN
- Alpha Go
- AlphaZero-nature
- TD3
- NAF
- TCN - Contrastive Networks):Sermanet, et al, 2017
- Reinforcement and Imitation Learning
- Unifying Count-Based Exploration and Intrinsic Motivation
- Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
- Action-Conditional Video Prediction using Deep Networks in Atari Games
- Control of Memory, Active Perception, and Action in Minecraft
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- NAF
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- DQN-nature - Network ); Mnih et al, 2015
- AlphaZero-nature
- PathNet
- Reinforcement and Imitation Learning
- Unifying Count-Based Exploration and Intrinsic Motivation
- Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
- Action-Conditional Video Prediction using Deep Networks in Atari Games
- plannet
- AlphaZero-nature
- DPG
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
- DQN-nature - Network ); Mnih et al, 2015
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Algorithm Repos
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Project
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Implementation of Algorithms
- DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills
- SFV
- [code
- StarCraft II - pysc2 Deep Reinforcement Learning Examples
- An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
- Using reinforcement learning to teach a car to avoid obstacles
- SFV
- A reinforcement learning algorithm for the 2048 game
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Awesome
- 强化学习从入门到放弃的资料
- Reinforcement learning resources curated
- This project is for learning and researching on Deep RL. Maintained by University AI researchers
- Reinforcement Learning Notebooks
- Awesome Reinforcement Learning(RL) for Natural Language Processing(NLP))
- TensorFlow implementation of Deep Reinforcement Learning papers
- A list of recent papers regarding deep reinforcement learning
- Paper list of multi-agent reinforcement learning (MARL) )
- Deep Reinforcement Learning(深度强化学习)
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强化学习实战资源
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Implementation of Algorithms
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course
- Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
- Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
- PyTorch 实现 DQN, AC, A2C, A3C, , Policy Gradient, DDPG, TRPO, PPO, ACER
- Repo for the Deep Reinforcement Learning Nanodegree program
- Deep Reinforcement learning framework
- PyTorch implementations of various DRL algorithms for both single agent and multi-agent
- Codes for understanding Reinforcement Learning( updating... )
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
- 教程 | 如何在Unity环境中用强化学习训练Donkey Car
- 深入浅出解读"多巴胺（Dopamine）论文"、环境配置和实例分析
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Keywords
reinforcement-learning
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deep-reinforcement-learning
9
pytorch
5
tensorflow
4
ppo
4
machine-learning
3
openai-gym
3
policy-gradient
3
dqn
3
deep-q-network
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actor-critic
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double-dqn
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multiagent-reinforcement-learning
2
deep-recurrent-q-network
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alphago
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gym
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reinforcement-learning-algorithms
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python
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a2c
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dueling-dqn
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trpo
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sarsa
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q-learning
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neural-networks
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drqn
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deep-learning-algorithms
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deep-deterministic-policy-gradient
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asynchronous-advantage-actor-critic
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toolbox
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hindsight-experience-replay
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markov-decision-processes
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keras
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theano
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aaai
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aamas
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agi
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aistats
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artificial-general-intelligence
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distributional
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exploration-exploitation
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game
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hierarchical-reinforcement-learning
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iclr
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icml
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ijcai
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inverse-rl
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planning
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reward
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theoretical-computer-science
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uai
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