2 papers
cs.LG2025
Quantile Q-Learning: Revisiting Offline Extreme Q-Learning with Quantile Regression
Xinming Gao, Shangzhe Li, Yujin Cai +1
Offline reinforcement learning (RL) enables policy learning from fixed datasets without further environment interaction, making it particularly valuable in high-risk or costly doma…
cs.MA2025
Distributed Neural Policy Gradient Algorithm for Global Convergence of Networked Multi-Agent Reinforcement Learning
Pengcheng Dai, Yuanqiu Mo, Wenwu Yu +1
This paper studies the networked multi-agent reinforcement learning (NMARL) problem, where the objective of agents is to collaboratively maximize the discounted average cumulative…