閱讀Qatten：A General Framework for Cooperative Multiagent Reinforcement Learning
寫在前面：還是那句話，不要怕理論，一個知識點一個知識點地理解。胡適說：「怕什麼真理無窮，進一步有一步的歡喜」。 目錄 題目作者 摘要 方法 理論證明 實際方法 實驗 寫在後面 題目作者 2020.06，arXiv，v2。天津大學Jianye Hao老師組的工作，一作的Yaodong Yang也很厲害,可以重點關注郝老師他們組裏的工作。 摘要 這篇同樣是值分解路線下的一篇工作，作者認爲之前的VDN,
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相關文章
- 1. 閱讀QTRAN:Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
- 2. FeUdal Networks for Hierarchical Reinforcement Learning 閱讀筆記
- 3. 論文閱讀：DRN: A Deep Reinforcement Learning Framework for News Recommendation
- 4. Deep Reinforcement Learning for Dialogue Generation閱讀筆記
- 5. Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
- 6. 讀文獻 Large Scale Learning of General Visual Representations for Transfer 閱讀心得
- 7. 論文閱讀15：Massively Parallel Methods for Deep Reinforcement Learning
- 8. 論文閱讀：(LIRD)Deep Reinforcement Learning for List-wise Recommendations
- 9. 【論文閱讀】Discovering Reinforcement Learning Algorithms
- 10. Value-Decomposition Networks For Cooperative Multi-Agent Learning筆記