Learning to Schedule Communication in Multi-agent Reinforcement Learning

1 code implementation • ICLR 2019 • Daewoo Kim, Sangwoo Moon, David Hostallero, Wan Ju Kang, Taeyoung Lee, Kyunghwan Son, Yung Yi

Many real-world reinforcement learning tasks require multiple agents to make sequential decisions under the agents' interaction, where well-coordinated actions among the agents are crucial to achieve the target goal better at these tasks.

Multi-agent Reinforcement Learning reinforcement-learning +2