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멀티 에이전트 강화학습 기술 동향
A Survey on Recent Advances in Multi-Agent Reinforcement Learning 원문보기

전자통신동향분석 = Electronics and telecommunications trends, v.35 no.6, 2020년, pp.137 - 149  

유병현 (복합지능연구실) ,  데브라니 데비 (정보전략부) ,  김현우 (복합지능연구실) ,  송화전 (복합지능연구실) ,  박경문 (복합지능연구실) ,  이성원 (정보전략부)

Abstract ▼ AI-Helper 아이콘AI-Helper

Several multi-agent reinforcement learning (MARL) algorithms have achieved overwhelming results in recent years. They have demonstrated their potential in solving complex problems in the field of real-time strategy online games, robotics, and autonomous vehicles. However these algorithms face many c...

주제어

#멀티 에이전트 강화학습   #에이전트 간 관계 모델링   #에이전트 간 신뢰할당   #에이전트 간 통신   #탐색-이용 딜레마   #MARL 실험 환경  

표/그림 (4)

참고문헌 (31)

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    상세보기 crossref

  18. E. Pesce and G. Montana, "Improving coordination in smallscale multi-agent deep reinforcement learning through memory-driven communication," Mach. Learn. vol. 109, 2020, doi: 10.1007/s10994-019-05864-5. 

    상세보기 crossref

  19. S. Q. Zhang, Q. Zhang, and J. Lin, "Efficient communication in multi-agent reinforcement learning via variance based control," in Adv. Neural Inform. Process. Syst. 2019, pp. 3235-3244. 

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  31. M. Samvelyan et al., "The starcraft multi-agent challenge," arXiv preprint, CoRR, 2019, arXiv: 1902.04043. 

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