4 papers
Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows
Wenhao Li, Bo Jin, Mingyi Hong +2
This position paper argues that optimization problem solving can transition from expert-dependent to evolutionary agentic workflows. Traditional optimization practices rely on huma…
Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding
Shiyue Wang, Haozheng Xu, Yuhan Zhang +4
Multi-Agent Path Finding (MAPF) is a fundamental problem in artificial intelligence and robotics, requiring the computation of collision-free paths for multiple agents navigating f…
SkyRover: A Modular Simulator for Cross-Domain Pathfinding
Wenhui Ma, Wenhao Li, Bo Jin +2
Unmanned Aerial Vehicles (UAVs) and Automated Guided Vehicles (AGVs) increasingly collaborate in logistics, surveillance, inspection tasks and etc. However, existing simulators oft…
GraphThought: Graph Combinatorial Optimization with Thought Generation
Zixiao Huang, Lifeng Guo, Wenhao Li +6
Graph combinatorial optimization (GCO) problems are central to domains like logistics and bioinformatics. While traditional solvers dominate, large language models (LLMs) offer new…