A Very Condensed Survey and Critique of Multiagent Deep Reinforcement Learning

  • Conference on Autonomous Agents and Multi-Agent Systems 2020 International (Creator)
  • Theodor Cimpeanu (Teesside University) (Creator)
  • The Anh Han (Creator)



Deep reinforcement learning (RL) has achieved outstanding results in recent years. This has led to a dramatic increase in the number of applications and methods. Recent works have explored learning beyond single-agent scenarios and have considered multiagent learning (MAL) scenarios. The primary goal of this article is to provide a clear overview of current multiagent deep reinforcement learning (MDRL) literature.
Date made available1 Jan 2020
PublisherUnderline Science Inc.

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