Boolean Satisfiability Problem

The Boolean Satisfiability Problem (SAT) involves determining if there exists an assignment of truth values to variables that satisfies a given Boolean formula. Current research focuses on improving the efficiency of SAT solvers, exploring novel algorithms like those based on integer programming and reinforcement learning, graph neural networks, and integrating machine learning techniques to enhance heuristic strategies and learn effective encodings. These advancements are crucial for optimizing various applications heavily reliant on SAT solving, including electronic design automation, artificial intelligence, and constraint satisfaction problems, ultimately impacting the speed and scalability of these fields.