3 papers
cs.LG2026
Transferable Delay-Aware Reinforcement Learning via Implicit Causal Graph Modeling
Chenran Zhao, Dianxi Shi, Yaowen Zhang +2
Random delays weaken the temporal correspondence between actions and subsequent state feedback, making it difficult for agents to identify the true propagation process of action ef…
cs.LG2026
Delay-Empowered Causal Hierarchical Reinforcement Learning
Chenran Zhao, Dianxi Shi, Haotian Wang +4
Many real-world tasks involve delayed effects, where the outcomes of actions emerge after varying time lags. Existing delay-aware reinforcement learning methods often rely on state…
cs.LG2025
D3HRL: A Distributed Hierarchical Reinforcement Learning Approach Based on Causal Discovery and Spurious Correlation Detection
Chenran Zhao, Dianxi Shi, Mengzhu Wang +5
Current Hierarchical Reinforcement Learning (HRL) algorithms excel in long-horizon sequential decision-making tasks but still face two challenges: delay effects and spurious correl…