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+have+demonstrated+impressive+accomplishments+in+both+reasoning+and+planning%252C+their+abilities+in+multi-agent+collaborations+remains+largely+unexplored.+This+study+evaluates+LLM-based+agents+in+a+multi-agent+cooperative+text+game+with+Theory+of+Mind+(ToM)+inference+tasks%252C+comparing+their+performance+with+Multi-Agent+Reinforcement+Learning+(MARL)+and+planning-based+baselines.+We+observed+evidence+of+emergent+collaborative+behaviors+and+high-order+Theory+of+Mind+capabilities+among+LLM-based+agents.+Our+results+reveal+limitations+in+LLM-based+agents%27+planning+optimization+due+to+systematic+failures+in+managing+long-horizon+contexts+and+hallucination+about+the+task+state.+We+explore+the+use+of+explicit+belief+state+representations+to+mitigate+these+issues%252C+finding+that+it+enhances+task+performance+and+the+accuracy+of+ToM+inferences+for+LLM-based+agents.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.95a8fdfb38d33fe987cfedcff42c5f58%3frik%3d%252bsJCRM0BJxMxzA%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Multi-Agent+Game+Theory+LLM&FORM=IRPRST&ck=EACDD92A78F2D71EE4AE831777C3AD35&selectedIndex=14&itb=0)
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