Max Sat

Max-SAT (Maximum Satisfiability) is a fundamental optimization problem focused on finding an assignment of Boolean variables that satisfies the maximum number of clauses in a Boolean formula. Current research emphasizes developing efficient algorithms, including quantum-inspired approaches and those leveraging deep learning, particularly graph neural networks, to solve Max-SAT and related problems like Max-2-SAT. This research is driven by the need for improved solutions to various combinatorial optimization problems across diverse fields, from resource allocation in multi-agent systems to the synthesis of cost-optimal systems, where Max-SAT serves as a powerful modeling framework. The development of more efficient and generalizable Max-SAT solvers has significant implications for advancing these applications.