Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces

9 August 2021

Papers citing "Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces"

6 / 6 papers shown

Title
Safe Multi-Agent Reinforcement Learning for Formation Control without Individual Reference Targets Murad Dawood Sicong Pan Nils Dengler Siqi Zhou Angela P. Schoellig Maren Bennewitz OffRL 32 3 0 20 Dec 2023
Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning Matej Jusup Barna Pásztor Tadeusz Janik Kecheng Zhang F. Corman Andreas Krause Ilija Bogunovic 29 3 0 29 Jun 2023
Emergent Incident Response for Unmanned Warehouses with Multi-agent Systems* Yibo Guo Mingxin Li Jingting Zong Mingliang Xu 24 0 0 29 May 2023
Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges Ziyuan Zhou Guanjun Liu Ying-Si Tang 33 14 0 17 May 2023
A Review of Safe Reinforcement Learning: Methods, Theory and Applications Shangding Gu Longyu Yang Yali Du Guang Chen Florian Walter Jun Wang Alois C. Knoll OffRL AI4TS 115 237 0 20 May 2022
DeCOM: Decomposed Policy for Constrained Cooperative Multi-Agent Reinforcement Learning Zhaoxing Yang Rong Ding Haiming Jin Yifei Wei Haoyi You Guiyun Fan Xiaoying Gan Xinbing Wang 32 4 0 10 Nov 2021