Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning

2 April 2020

Papers citing "Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning"

6 / 6 papers shown

Title
Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning Hadi Nekoei Akilesh Badrinaaraayanan Amit Sinha Mohammad Amini Janarthanan Rajendran Aditya Mahajan Sarath Chandar 31 13 0 06 Feb 2023
Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning Pedro P. Santos Diogo S. Carvalho Miguel Vasco Alberto Sardinha Pedro A. Santos Ana Paiva Francisco S. Melo 21 1 0 12 Oct 2022
Common Information based Approximate State Representations in Multi-Agent Reinforcement Learning Shitao Xiao V. Subramanian 29 9 0 25 Oct 2021
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning Weichao Mao Lin F. Yang Kaipeng Zhang Tamer Bacsar 39 57 0 12 Oct 2021
Federated Reinforcement Learning: Techniques, Applications, and Open Challenges Jiaju Qi Qihao Zhou Lei Lei Kan Zheng FedML 31 145 0 26 Aug 2021
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan H. Zha 25 21 0 17 Apr 2020