Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization
This review examines how machine learning can control quantum optimization workflows to create adaptive pipelines. It categorizes approaches into AI for Quantum Optimization, Quantum for AI-Driven Optimization, and AI–Quantum CoOptimization. The paper highlights that while different paradigms have strengths, the field is moving toward adaptive hybrid solvers that dynamically choose the right formulation and resources.