SOURCE-LINKED INTELLIGENCE
Extending SMT Solving with Non-Ground Clause Learning
Quantifier instantiation is currently the main approach to non-ground SMT solving: solvers generate ground instances and solve the resulting ground SMT problems with CDCL(T)-style reasoning. When a conflict is found, conflict analysis learns only a ground clause, even though the conflict comes from instances of non-ground clauses. Yet non-ground reasoning can give exponentially shorter proofs than purely ground reasoning. We propose a calculus that consists of ground instantiations, CDCL(T)-style rules, and non-ground conflict analysis. The solver reasons on ground instances, but the resolutio
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T13:17:14.000Z
First collected: 2026-09-20T19:02:05.452Z. This is not the publication date.