Monte Carlo Graph Coloring
Artificial Intelligence
2025-04-07 v1
Abstract
Graph Coloring is probably one of the most studied and famous problem in graph algorithms. Exact methods fail to solve instances with more than few hundred vertices, therefore, a large number of heuristics have been proposed. Nested Monte Carlo Search (NMCS) and Nested Rollout Policy Adaptation (NRPA) are Monte Carlo search algorithms for single player games. Surprisingly, few work has been dedicated to evaluating Monte Carlo search algorithms to combinatorial graph problems. In this paper we expose how to efficiently apply Monte Carlo search to Graph Coloring and compare this approach to existing ones.
Keywords
Cite
@article{arxiv.2504.03277,
title = {Monte Carlo Graph Coloring},
author = {Tristan Cazenave and Benjamin Negrevergne and Florian Sikora},
journal= {arXiv preprint arXiv:2504.03277},
year = {2025}
}