Shumao Zhai

Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning

We propose RDC-SAT, a novel approach to optimize splitting heuristics in Divide-and-Conquer SAT solvers using deep reinforcement learning. Our method dynamically extracts features from the current solving state whenever a split is required. These features, such as learned clauses, variable activit…