4 papers
OptiTree: Hierarchical Thoughts Generation with Tree Search for LLM Optimization Modeling
Haoyang Liu, Jie Wang, Yuyang Cai +3
Optimization modeling is one of the most crucial but technical parts of operations research (OR). To automate the modeling process, existing works have leveraged large language mod…
Advancing Symbolic Discovery on Unsupervised Data: A Pre-training Framework for Non-degenerate Implicit Equation Discovery
Kuang Yufei, Wang Jie, Huang Haotong +5
Symbolic regression (SR) -- which learns symbolic equations to describe the underlying relation from input-output pairs -- is widely used for scientific discovery. However, a rich…
Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics
Hongyu Liu, Haoyang Liu, Yufei Kuang +2
Combinatorial optimization (CO) is one of the most fundamental mathematical models in real-world applications. Traditional CO solvers, such as Branch-and-Bound (B&B) solvers, heavi…
Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
Qianmei Liu, Yufei Kuang, Jie Wang
Deep reinforcement learning (DRL) algorithms can suffer from modeling errors between the simulation and the real world. Many studies use adversarial learning to generate perturbati…