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Found 3 papers, 2 papers with code
Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing
The size of the observed neighborhood limits the generalizability to different graphs and affects the reactivity of agents, the quality of the selected actions, and the communication overhead.
Learning to Cooperate and Communicate Over Imperfect Channels
In addition to this message size selection, agents learn to encode and decode messages to improve their jointly trained policies.
Know your Enemy: Investigating Monte-Carlo Tree Search with Opponent Models in Pommerman
In combination with Reinforcement Learning, Monte-Carlo Tree Search has shown to outperform human grandmasters in games such as Chess, Shogi and Go with little to no prior domain knowledge.
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