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4. Stabilizing Multi-Agent Deep Reinforcement Learning By Implicitly Estimating Other Agents’ Behaviors

Stabilizing Multi-Agent Deep Reinforcement Learning By Implicitly Estimating Other Agents’ Behaviors

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IEEE ICASSP 2020 Virtual Conference May 2020

Deep reinforcement learning (DRL) is able to learn control policies for many complicated tasks, but it?s power has not been unleashed to handle multi-agent circumstances. Independent learning, where each agent treats others as part of the environment and

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Stabilizing Multi-Agent Deep Reinforcement Learning By Implicitly Estimating Other Agents’ Behaviors

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Deep reinforcement learning (DRL) is able to learn control policies for many complicated tasks, but it?s power has not been unleashed to handle multi-agent circumstances. Independent learning, where each agent treats others as part of the environment and