可以是，而且每个agent理应对环境观察都是自己的局部观察（可以理解为从自己的视角去看环境，那么每个智能体看到的环境信息应该是不一样的），对应的采取的动作是也应该可以不一样。例如，MADDPG中每个agent（actor网络）都是接受环境的局部信息，做出自己的判断。
Decision making of an agent depends on the other agents' behavior while sharing information is not always possible. On the other hand, predicting other agents' policies while they are also learning is a difficult task. Also, some agents in a multi-agent environment may not behave rationally. ...
为什么说TPP协议是MultiAgent的最终形态?因为它彻底抛弃了工具的概念,将工具转变为Action,并给它安装了”大脑“,相比MCP和其他智能体平台或框架,由于有了”大脑“,工具在运行时不可用或者不好用的情况下实现自我优化。为了做到这一点,TPP提出了Anything is Action,将工具内部逻辑内化为一系列Action,创造了Coordinator机制...
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Agent cooperationSelf-playCross-playThe card gameHanabiis considered a strong medium for the testing and development of multi-agent reinforcement learning (MARL) algorithms, due to its cooperative nature, partial observability, limited communication and remarkable complexity. Previous research efforts have ...
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This repo contains code and models for "Other-Play" for Zero-Shot Coordination and Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning.To reference these works, please use:Other-Play@incollection{icml2020_5369, author = {Hu, Hengyuan and Peysakhovich, Alexander and Lerer, Adam...
for cooperative sequences in multi-agentsystems, discusses the different categories of concurrent actions, and proposes somerules for situation revision and an algorithm used to generate resulting situations.An example is also given to show how to solve concurrent problems occurring inmulti-agent ...
Code supporting the paper Efficient Multiagent Planning via Shared Action Suggestions. - dylan-asmar/estimated_joint_belief