阅读QTRAN:Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
写在前面：这篇文章我也是前前后后看了几遍，还在网上找了一些资料，但是感觉始终也没太看明白，就先把目前的理解写在这里，等以后有了新的理解再更新。要强调一点的是，这篇文章我刚读的时候是真的超级懵，但是不放弃偶尔就读偶尔就读，再结合别人的理解确实还是会有逐渐深入的理解的，所以以后遇到难的文章也不要丧气，平常心慢慢来（当然主要可能还是我的水平不行，读起来才这么难，hh） 目录 题目作者 摘要 相关工作介绍
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相关文章
- 1. 阅读Qatten：A General Framework for Cooperative Multiagent Reinforcement Learning
- 2. Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
- 3. FeUdal Networks for Hierarchical Reinforcement Learning 阅读笔记
- 4. Deep Reinforcement Learning for Dialogue Generation阅读笔记
- 5. 论文阅读笔记《Ranking Sentences for Extractive Summarization with Reinforcement Learning》
- 6. 阅读《SeedNet: Automatic Seed Generation with Deep Reinforcement Learning for Robust Interactive Segme》
- 7. RL论文阅读【四】Deep Reinforcement Learning with Double Q-learning（Double DQN）
- 8. Introduction to Reinforcement Learning
- 9. Reinforcement Learning for Relation Classification from Noisy Data阅读笔记
- 10. 解读continuous control with deep reinforcement learning（DDPG）