3 papers
cs.LG2026
SCALAR: Learning and Composing Skills through LLM Guided Symbolic Planning and Deep RL Grounding
Renos Zabounidis, Yue Wu, Simon Stepputtis +4
LM-based agents excel when given high-level action APIs but struggle to ground language into low-level control. Prior work has LLMs generate skills or reward functions for RL, but…
stat.ML2025
POLAR: A Pessimistic Model-based Policy Learning Algorithm for Dynamic Treatment Regimes
Ruijia Zhang, Xiangyu Zhang, Zhengling Qi +2
Dynamic treatment regimes (DTRs) provide a principled framework for optimizing sequential decision-making in domains where decisions must adapt over time in response to individual…
cs.LG2024
MoMA: Model-based Mirror Ascent for Offline Reinforcement Learning
Mao Hong, Zhiyue Zhang, Yue Wu +1
Model-based offline reinforcement learning methods (RL) have achieved state-of-the-art performance in many decision-making problems thanks to their sample efficiency and generaliza…