3 papers
cs.AI2026
Diffusion-Guided Uncertainty-Aware Delayed Policy Optimization
Junqi Tu, Zejiao Liu, Fangfei Li +1
Reinforcement learning in real world environments often suffers from severe performance degradation due to delayed feedback. Existing approaches typically mitigate performance degr…
cs.LG2025
HCPO: Hierarchical Conductor-Based Policy Optimization in Multi-Agent Reinforcement Learning
Zejiao Liu, Junqi Tu, Yitian Hong +4
In cooperative Multi-Agent Reinforcement Learning (MARL), efficient exploration is crucial for optimizing the performance of joint policy. However, existing methods often update jo…
cs.AI2025
Robust and Efficient Communication in Multi-Agent Reinforcement Learning
Zejiao Liu, Yi Li, Jiali Wang +6
Multi-agent reinforcement learning (MARL) has made significant strides in enabling coordinated behaviors among autonomous agents. However, most existing approaches assume that comm…