3 citations · 5 across the 13 of their papers we have counts for
13 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…
Hierarchical Learning-based Graph Partition for Large-scale Vehicle Routing Problems
Yuxin Pan, Ruohong Liu, Yize Chen +2
Neural solvers based on the divide-and-conquer approach for Vehicle Routing Problems (VRPs) in general, and capacitated VRP (CVRP) in particular, integrates the global partition of…
SEAL: SEmantic-Augmented Imitation Learning via Language Model
Chengyang Gu, Yuxin Pan, Haotian Bai +2
Hierarchical Imitation Learning (HIL) is a promising approach for tackling long-horizon decision-making tasks. While it is a challenging task due to the lack of detailed supervisor…
C-MORL: Multi-Objective Reinforcement Learning through Efficient Discovery of Pareto Front
Ruohong Liu, Yuxin Pan, Linjie Xu +4
Multi-objective reinforcement learning (MORL) excels at handling rapidly changing preferences in tasks that involve multiple criteria, even for unseen preferences. However, previou…
Learning and Optimization for Price-based Demand Response of Electric Vehicle Charging
Chengyang Gu, Yuxin Pan, Ruohong Liu +1
In the context of charging electric vehicles (EVs), the price-based demand response (PBDR) is becoming increasingly significant for charging load management. Such response usually…
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
Yuxin Pan, Yize Chen, Fangzhen Lin
Designing effective policies for the online 3D bin packing problem (3D-BPP) has been a long-standing challenge, primarily due to the unpredictable nature of incoming box sequences…
Laxity-Aware Scalable Reinforcement Learning for HVAC Control
Ruohong Liu, Yuxin Pan, Yize Chen
Demand flexibility plays a vital role in maintaining grid balance, reducing peak demand, and saving customers' energy bills. Given their highly shiftable load and significant contr…
Backward Imitation and Forward Reinforcement Learning via Bi-directional Model Rollouts
Yuxin Pan, Fangzhen Lin
Traditional model-based reinforcement learning (RL) methods generate forward rollout traces using the learnt dynamics model to reduce interactions with the real environment. The re…