Researchers proposed Collab-Solver, a novel multi-agent-based policy learning framework for mixed-integer linear programming (MILP). This framework enables collaborative policy optimization for multiple modules, leading to improved solving performance and generalization abilities. This development may be of interest to researchers and developers working on AI optimization techniques and their applications.