Multi-agent reinforcement learning
PulseAugur coverage of Multi-agent reinforcement learning — every cluster mentioning Multi-agent reinforcement learning across labs, papers, and developer communities, ranked by signal.
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Survey maps graph neural networks in multi-agent reinforcement learning
This paper surveys recent advancements in multi-agent reinforcement learning (MARL) that utilize graph neural networks (GNNs) for agent communication. It highlights how GNNs, when applied to interaction graphs, enable a…
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AI research analyzes coordination gap in job-shop scheduling training methods
A new paper analyzes the trade-offs between joint and modular training for multi-agent reinforcement learning in job-shop scheduling with transportation resources. The research quantifies the "coordination gap" between …
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MARL enables robots to cooperatively monitor indoor environments
Researchers have developed a new multi-agent reinforcement learning framework for robots to cooperatively monitor indoor environments. This approach optimizes robot movement to directly enhance monitoring accuracy, unli…