8 papers
TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning
Siyang Li, Yize Chen, Zijie Zhu +4
Time Series Foundation Models (TSFMs) have demonstrated strong generalization capability and data efficiency in time series forecasting through large-scale pretraining. However, ad…
A Pontryagin Method of Model-based Reinforcement Learning via Hamiltonian Actor-Critic
Chengyang Gu, Yuxin Pan, Hui Xiong +1
Model-based reinforcement learning (MBRL) improves sample efficiency by leveraging learned dynamics models for policy optimization. However, the effectiveness of methods such as ac…
STO-RL: Offline RL under Sparse Rewards via LLM-Guided Subgoal Temporal Order
Chengyang Gu, Yuxin Pan, Hui Xiong +1
Offline reinforcement learning (RL) enables policy learning from pre-collected datasets, avoiding costly and risky online interactions, but it often struggles with long-horizon tas…
A Computable Game-Theoretic Framework for Multi-Agent Theory of Mind
Fengming Zhu, Yuxin Pan, Xiaomeng Zhu +1
Originating in psychology, (ToM) has attracted significant attention across multiple research communities, especially logic, economics, and robotics. Most…
Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP
Yuxin Pan, Zhiguang Cao, Chengyang Gu +4
Existing neural methods for multi-task vehicle routing problems (VRPs) typically learn unified solvers to handle multiple constraints simultaneously. However, they often underutili…
Vertex-Guided Redundant Constraints Identification for Unit Commitment
Xuan He, Yuxin Pan, Yize Chen +1
Power systems Unit Commitment (UC) problem determines the generator commitment schedule and dispatch decisions to realize the reliable and economic operation of power networks. The…