Learning a SAT Solver from Single-Bit Supervision

ICLR 2019 Daniel SelsamMatthew LammBenedikt BünzPercy LiangLeonardo de MouraDavid L. Dill

We present NeuroSAT, a message passing neural network that learns to solve SAT problems after only being trained as a classifier to predict satisfiability. Although it is not competitive with state-of-the-art SAT solvers, NeuroSAT can solve problems that are substantially larger and more difficult than it ever saw during training by simply running for more iterations... (read more)

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