arXiv subjects

Fredrik Rømming

Publications and source records attributed to Fredrik Rømming.

3 recordsLinked to original sources

arXiv2026

Reset Early, Reset Often, Eliminate Models

Connection-tableau provers typically construct closed tableaux by backtracking search. This gives lightweight proof procedures, but their low-memory search state leaves little derived information to reuse after a failed attempt. SATCoP addresses this by retaining grounded tableau clauses in an incremental SAT solver, allowing the prover to refute the problem once the accumulated ground clauses become propositionally unsatisfiable. We introduce SATResetCoP, which relies more directly on this persistent SAT state by not backtracking on unproductive tableaux and instead starting new ones to generate further ground clauses for the SAT solver. On TPTP, SATResetCoP improves over our leanCoP-style baseline by 54% and our SATCoP-style baseline by 18%. On the bushy MPTP2078 benchmark, it solves 616 problems, a 49% improvement over our leanCoP-style baseline and a 12% improvement over our SATCoP-style baseline. These results suggest that changing tableau guidance to accumulate useful ground clauses faster improves the performance of the prover.

cs.LO↗

arXiv2026

Imitation Learning for Connection-Tableau Construction

An automated theorem prover builds a proof step by step, choosing at each point what to add and what to remove. We cast this construction as a policy acting in a transition system induced by a formal calculus, which fixes which steps are sound: for clausal connection tableaux, leanCoP-style search and plCoP/rlCoP-style planning then become stateful policies over one interface, and policy-learning methods apply directly. We equip such policies with a graph neural network that scores proof edits from structure that transfers across problems, train it by imitation learning from found proofs, and measure how performance holds as we remove search scaffolding, from full symbolic backtracking to a policy the network drives alone. Within a fixed step budget on M2k, MPTP2078-bushy, and TPTP v9.2.1, learned policies solve up to 46% more problems than leanCoP, and reach proofs in an order of magnitude fewer steps.

cs.AI↗

arXiv2023

Symbolic Analysis and Parameter Synthesis for Time Petri Nets Using Maude and SMT Solving

Parametric time Petri nets with inhibitor arcs (PITPNs) support flexibility for timed systems by allowing parameters in firing bounds. In this paper we present and prove correct a concrete and a symbolic rewriting logic semantics for PITPNs. We show how this allows us to use Maude combined with SMT solving to provide sound and complete formal analyses for PITPNs. We develop a new general folding approach for symbolic reachability that terminates whenever the parametric state-class graph of the PITPN is finite. We explain how almost all formal analysis and parameter synthesis supported by the state-of-the-art PITPN tool Roméo can be done in Maude with SMT. In addition, we also support analysis and parameter synthesis from parametric initial markings, as well as full LTL model checking and analysis with user-defined execution strategies. Experiments on three benchmarks show that our methods outperform Roméo in many cases.

cs.LO↗