CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound

This article likely discusses a novel approach to solving Mixed Integer Linear Programming (MILP) problems using Reinforcement Learning (RL). The core idea seems to be leveraging RL to learn policies that guide the Branch and Bound algorithm, a common method for solving MILPs. The use of 'Branch and Bound' suggests a focus on optimization and finding optimal solutions. The source, ArXiv, indicates this is a research paper, likely presenting new findings and methodologies.