AIBullisharXiv – CS AI · 7h ago7/10
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Stop Wandering, Find the Keys: LLMs Discriminate Key States for Efficient Multi-Agent Exploration
Researchers introduce LEMAE, a novel multi-agent reinforcement learning framework that leverages Large Language Models to identify critical 'key states' in complex environments, enabling agents to explore more efficiently with 10x acceleration in certain scenarios. The approach combines LLM-guided state discrimination with a Key State Memory Tree to reduce redundant exploration and improve performance on challenging benchmarks like SMAC and MPE.