LTS-CG infers latent temporal sparse coordination graphs from historical observations to enable efficient, uncertainty-aware agent coordination in MARL with complexity linear in the number of agents.
Value-decomposition networks for cooperative multi-agent learning based on JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, 2024 13 team reward
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Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning
LTS-CG infers latent temporal sparse coordination graphs from historical observations to enable efficient, uncertainty-aware agent coordination in MARL with complexity linear in the number of agents.