Achieving Near-Optimal Individual Regret & Low Communications in Multi-Agent Bandits
Achieving Near-Optimal Individual Regret & Low Communications in Multi-Agent Bandits
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发表时间：
2023
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通讯作者：
Xuchuang Wang;L. Yang;Y. Chen;Xutong Liu;M. Hajiesmaili;D. Towsley;John C.S. Lui
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作者：
Xuchuang Wang;L. Yang;Y. Chen;Xutong Liu;M. Hajiesmaili;D. Towsley;John C.S. Lui
合作多智能体多武装土匪（CMA 2B）研究如何分布式代理合作发挥相同的多武装土匪游戏。现有的大多数CMA 2B工作都集中在最大化所有代理的群体绩效-所有代理的个人绩效的累积（即
Cooperative multi-agent multi-armed bandits ( CMA2B ) study how distributed agents cooperatively play the same multi-armed bandit game. Most existing CMA2B works focused on maximizing the group performance of all agents—the accumulation of all agents’ individual performance (i