Boolean Satisfiability

Boolean satisfiability (SAT) focuses on determining whether there exists an assignment of truth values to variables that satisfies a given Boolean formula, a fundamental problem with broad applications in computer science. Current research emphasizes improving the efficiency and correctness of SAT solvers, exploring the use of graph neural networks (GNNs) and transformers to enhance solver performance and interpretability, and developing novel encoding techniques for diverse problem domains like multi-agent pathfinding and electronic design automation. These advancements are driving progress in areas such as automated verification, artificial intelligence planning, and circuit design, where efficient SAT solving is crucial.