Modeling Others using Oneself in Multi-Agent Reinforcement Learning
ICML-18的文章，前幾天我自己想的方法，就是對敵方和己方分別應用一個goal目標，只是我一直在考慮怎麼從state中抽離出兩個goal，而這篇文章思路的確很新奇，但是也有很明顯的侷限性。 老習慣，先上環境： 文章一共給了三個環境，第一個是coin，第二個是recipe，第三個是door 我先一個一個介紹環境設置，第一個環境是一個合作性質的環境 reward的設置： 有兩個agent a1和a2
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相關文章
- 1. 閱讀Qatten：A General Framework for Cooperative Multiagent Reinforcement Learning
- 2. Learning Policy Representations in Multiagent Systems
- 3. Policy in Reinforcement Learning
- 4. Policy Gradient Methods in Reinforcement Learning
- 5. Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning學習筆記
- 6. Framework of Automatic Text Summarization Using Reinforcement Learning
- 7. Reinforcement Learning Exercise 3.24
- 8. Fast deep reinforcement learning using online adjustments from the past
- 9. Reinforcement Learning（一）：introduction
- 10. Application of Opposition-Based Reinforcement Learning in Image Segmentation