【导读】Christine Doig是Anaconda公司的高级数据科学家。没错Anaconda就是那个著名的Python科学计算与发行管理软件。Christine Doig从最基本的强化学习概念开始介绍强化学习Python实践经验，并以强化学习中的经典任务--Cartpole问题作为学习的入门例子，讲解从环境搭建、模型训练再到最后的效果评估的结果。
▌简介
Cartpole描述的问题可以认为是：在一辆小车上竖立一根杆子，然后给小车一个推或者拉的力，使得杆子尽量保持平衡不滑倒。
更详细的描述可参见openai官网上关于Cartpole问题的解释：https://gym.openai.com/envs/CartPole-v0
▌强化学习用到的python库
- OpenAI Gym: Toolkit for developing and comparing reinforcement learningalgorithms. MIT License, Last commit: November 2017 baselines: high-quality implementations of reinforcement learning algorithms,MIT License, Last commit: November 2017
- TensorForce, A TensorFlow library for applied reinforcement learning, Apache 2,Last commit: November 2017
- DeepRL, Highly modularized implementation of popular deep RL algorithms byPyTorch, Apache 2 License, Last commit: November 2017
- RLlab, a framework for developing and evaluating reinforcement learningalgorithms, MIT License, Last commit: July 2017
- AgentNet, Python library for deep reinforcement learning usingTheano Lasagne, MIT License, Last commit: August 2017
- RLPy, the Reinforcement Learning Library for Education and Research,3-Clause BSD License, Last commit: April 2016.
- PyBrain, the Python Machine Learning Library, 3-Clause BSD License, Lastcommit: March 2016.
▌强化学习资源
- Reinforcement Learning courseby David Silver http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html
- https://blog.acolyer.org/2017/11/17/mastering-the-game-of-go-without-humanknowledge/
- https://keon.io/deep-q-learning/
- https://rishav1.github.io/reinlearning/2017/01/05/simple-swarm-intelligenceoptimization-for-cartpole-balancing-problem.html
- AlphaGo Zero's win, what itmeans, Fast Forward Labs: http:// blog.fastforwardlabs.com/2017/10/25/alphago-zero.html
- 更多可以查看专知以前推出的强化学习荟萃资料：
【专知荟萃23】深度强化学习RL知识资料全集（入门/进阶/论文/综述/代码/专家，附查看）
▌PPT内容
参考链接：
https://speakerdeck.com/chdoig/rl-pytexas-2017
▌特别提示-Python强化学习实战 PPT下载：
请关注专知公众号
- 后台回复“RLP” 就可以获取PPT下载链接
