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ACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning [article]

Hangyu Mao, Zhibo Gong, Yan Ni, Zhen Xiao
2017 arXiv   pre-print
In this paper, we propose an Actor-Coordinator-Critic Net (ACCNet) framework for solving "learning-to-communicate" problem.  ...  The ACCNet naturally combines the powerful actor-critic reinforcement learning technology with deep learning technology.  ...  Acknowledgments The authors would like to thank Xiangyu Liu, Weichen Ke, Chao Ma, Quanbin Wang, Yiping Song and the anonymous reviewers for their insightful comments.  ... 
arXiv:1706.03235v3 fatcat:ejrksp7d5rchlja76n7f3icyfi

Mixed Cooperative-Competitive Communication Using Multi-agent Reinforcement Learning [chapter]

Astrid Vanneste, Wesley Van Wijnsberghe, Simon Vanneste, Kevin Mets, Siegfried Mercelis, Steven Latré, Peter Hellinckx
2021 Lecture Notes in Networks and Systems  
By using communication between multiple agents in multi-agent environments, one can reduce the effects of partial observability by combining one agent's observation with that of others in the same dynamic  ...  In this paper, we apply differentiable inter-agent learning (DIAL), designed for cooperative settings, to a mixed cooperative-competitive setting.  ...  We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.  ... 
doi:10.1007/978-3-030-89899-1_20 fatcat:ren57xjauzfjhkbtkzhk6di4fe