3 papers
cs.LG2026
A Survey of Continual Reinforcement Learning
Chaofan Pan, Xin Yang, Yanhua Li +4
Reinforcement Learning (RL) is an important machine learning paradigm for solving sequential decision-making problems. Recent years have witnessed remarkable progress in this field…
cs.LG2025
TECM*: A Data-Driven Assessment to Reinforcement Learning Methods and Application to Heparin Treatment Strategy for Surgical Sepsis
Jiang Liu, Yujie Li, Chan Zhou +11
Objective: Sepsis is a life-threatening condition caused by severe infection leading to acute organ dysfunction. This study proposes a data-driven metric and a continuous reward fu…
cs.LG2025
Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning
Zengxia Guo, Bohui An, Zhongqi Lu
Federated reinforcement learning (FRL) methods usually share the encrypted local state or policy information and help each client to learn from others while preserving everyone's p…