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DACOM: Learning Delay-Aware Communication for Multi-Agent Reinforcement Learning

AAAI 2023 · Multi-agent systems and games › Cooperative multi-agent RL · approach: Learned inter-agent communication · 20 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Adapt waiting time to network state with TimeNetDACOM · Cooperative Navigation and Predator-Preynormalized rewardHelped
Adapt communication waiting time to delayDACOM · Traffic Control intersectioncollision rateHelped
Adapt communication waiting time to delayDACOM · Traffic Control intersectionarrival rateHelped
Use communication without accounting for communication delaycommunication-based MARL · Delay-sensitive tasks and high-delay environmentsrewardHurt
Use a fixed waiting timer instead of adapting it to network conditionsACML · Low-delay environments (approximately 10%)rewardHurt
Use communication rather than no communicationDACOM · Predator-Prey, mean delay ratio greater than 70%rewardNo clear effect
Use adaptive delay-aware communicationDACOM · SMAC 3m and 8mwin rateNo clear effect
Use a fixed timer to limit waitingACML and ATOC · Increasing communication delaysrewardHelped

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