2 papers
cs.MA2025
Maximum Entropy Heterogeneous-Agent Reinforcement Learning
Jiarong Liu, Yifan Zhong, Siyi Hu +4
Multi-agent reinforcement learning (MARL) has been shown effective for cooperative games in recent years. However, existing state-of-the-art methods face challenges related to samp…
cs.LG2024
Revisiting Discrete Soft Actor-Critic
Haibin Zhou, Tong Wei, Zichuan Lin +6
We study the adaption of Soft Actor-Critic (SAC), which is considered as a state-of-the-art reinforcement learning (RL) algorithm, from continuous action space to discrete action s…