3 citations · 4 across the 14 of their papers we have counts for
5 papers · 1 filter
Formalizing Task-Space Complexity for Zero-Shot Generalization
Jung-Hoon Cho, Heling Zhang, Siqi Du +2
Policies must operate across diverse conditions, yet a single policy is often conservative while fully adaptive schemes can be complex. We study zero-shot generalization in context…
Learning to Segment for Vehicle Routing Problems
Wenbin Ouyang, Sirui Li, Yining Ma +1
Iterative heuristics are widely recognized as state-of-the-art for Vehicle Routing Problems (VRPs). In this work, we exploit a critical observation: a large portion of the solution…
RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations
Enrico Marchesini, Benjamin Donnot, Constance Crozier +7
Reinforcement learning (RL) can provide adaptive and scalable controllers essential for power grid decarbonization. However, RL methods struggle with power grids' complex dynamics,…
Towards Foundation Models for Mixed Integer Linear Programming
Sirui Li, Janardhan Kulkarni, Ishai Menache +2
Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-making problems but faces challenges in computational tractability and requires expert formulatio…
Model-Based Transfer Learning for Contextual Reinforcement Learning
Jung-Hoon Cho, Vindula Jayawardana, Sirui Li +1
Deep reinforcement learning (RL) is a powerful approach to complex decision making. However, one issue that limits its practical application is its brittleness, sometimes failing t…