LLM-generated coordination graph priors improve multi-agent reinforcement learning performance on MPE benchmarks, with models as small as 1.5B parameters proving effective.
Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
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Do LLM-derived graph priors improve multi-agent coordination?
LLM-generated coordination graph priors improve multi-agent reinforcement learning performance on MPE benchmarks, with models as small as 1.5B parameters proving effective.