How Actor-critic methods work part3(Machine Learning)
Communication-Efficient Actor-Critic Methods for Homogeneous Markov Games(arXiv) Author : Dingyang Chen, Yile Li, Qi Zhang Abstract : Recent success in cooperative multi-agent reinforcement learning (MARL) relies on centralized training and policy sharing. Centralized training eliminates the issue of non-stationarity MARL yet induces large communication costs, and policy sharing is empirically…
How Actor-critic methods work part3(Machine Learning) Communication-Efficient Actor-Critic Methods for Homogeneous Markov Games(arXiv) Author : Dingyang Chen, Yile Li, Qi Zhang Abstract : Recent success in cooperative multi-agent reinforcement learning (MARL) relies on centralized training and policy sharing. Centralized training eliminates the issue of non-stationarity MARL yet induces large communication costs, and policy sharing is empirically… deep-learning
Actorcritic method work part3Machine Learning CommunicationEfficient ActorCritic Methods Homogeneous Markov GamesarXiv Author Dingyang Chen Yile Li Qi Zhang Abstract Recent success cooperative multiagent reinforcement learning MARL relies centralized training policy sharing Centralized training eliminates issue nonstationarity MARL yet induces large communication cost policy sharing empirically… deeplearning