3 papers
cs.LG2026
SLOPE: Optimistic Potential Landscape Shaping for Model-based Reinforcement Learning
Yao-Hui Li, Zeyu Wang, Xin Li +7
Model-based reinforcement learning (MBRL) is sample-efficient but struggles in sparse reward settings. A critical bottleneck arises from the lack of informative gradients in sparse…
cs.LG2025
Wavelet Predictive Representations for Non-Stationary Reinforcement Learning
Min Wang, Xin Li, Ye He +4
The real world is inherently non-stationary, with ever-changing factors, such as weather conditions and traffic flows, making it challenging for agents to adapt to varying environm…
cs.LG2025
Revisiting Bisimulation Metric for Robust Representations in Reinforcement Learning
Leiji Zhang, Zeyu Wang, Xin Li +1
Bisimulation metric has long been regarded as an effective control-related representation learning technique in various reinforcement learning tasks. However, in this paper, we ide…