5 citations · 15 across the 8 of their papers we have counts for
4 papers · 1 filter
Decentralized Policy Optimization
Kefan Su, Zongqing Lu
The study of decentralized learning or independent learning in cooperative multi-agent reinforcement learning has a history of decades. Recently empirical studies show that indepen…
Multi-Agent Automated Machine Learning
Zhaozhi Wang, Kefan Su, Jian Zhang +4
In this paper, we propose multi-agent automated machine learning (MA2ML) with the aim to effectively handle joint optimization of modules in automated machine learning (AutoML). MA…
MA2QL: A Minimalist Approach to Fully Decentralized Multi-Agent Reinforcement Learning
Kefan Su, Siyuan Zhou, Jiechuan Jiang +3
Decentralized learning has shown great promise for cooperative multi-agent reinforcement learning (MARL). However, non-stationarity remains a significant challenge in fully decentr…
Divergence-Regularized Multi-Agent Actor-Critic
Kefan Su, Zongqing Lu
Entropy regularization is a popular method in reinforcement learning (RL). Although it has many advantages, it alters the RL objective of the original Markov Decision Process (MDP)…