AI RESEARCH
RLGT: A reinforcement learning framework for extremal graph theory
arXiv CS.LG
•
ArXi:2602.17276v2 Announce Type: replace Reinforcement learning (RL) is a subfield of machine learning that focuses on developing models that can autonomously learn optimal decision-making strategies over time. In a recent pioneering paper, Wagner nstrated how the Deep Cross-Entropy RL method can be applied to tackle various problems from extremal graph theory by reformulating them as combinatorial optimization problems. Subsequently, many researchers became interested in refining and extending the framework.