强化学习第一波学习资料整理

线上课程

• 李宏毅深度强化学习课程(2018)
• Deep Reinforcement Learning - Berkeley

代码实践

1. Reinforcement-Learning-Tutorial
2. Reinforcement Q-Learning from Scratch in Python with OpenAI Gym
3. Schooling Flappy Bird: A Reinforcement Learning Tutorial
4. Reinforcement Learning Tutorial Part 1: Q-Learning

1. DeepRL-Tutorials
2. Reinforcement_learning_tutorial_with_demo
3. basic_reinforcement_learning

顶刊论文

1. LeCun, Bengio and Hinton, Deep Learning, Nature, May 2015
2. Jordan and Mitchell, Machine learning: Trends, perspectives, and prospects, Science, July 2015
3. Michael Littman, Reinforcement learning improves behaviour from evaluative feedback, Nature, May 2015

综述论文

• Deep Reinforcement Learning: An Overview
  这篇论文概述了深度强化学习中一些最新精彩工作，主要说明了六个核心要素、六个重要机制和十二个有关应用。文章中先介绍了机器学习、深度学习和强化学习的背景，接着讨论了强化学习的核心要素，包括DQN网络、策略、奖励、模型、规划和搜索。
• 深度强化学习综述- 计算机学报

有趣论文

• Li, L., Chu, W., Langford, J., and Schapire, R. E. (2010). A contextual-bandit approach to personalized news article recommendation. In WWW.

深度博文

• 强化学习应用场景
• 强化学习落地：推荐系统