The performance of many hard combinatorial problem solvers depends strongly on their
parameter settings, and since manual parameter tuning is both tedious and suboptimal the …

Good parameter settings are crucial to achieve high performance in many areas of artificial
intelligence (AI), such as propositional satisfiability solving, AI planning, scheduling, and …

It is well known that different solution strategies work well for different types of instances of
hard combinatorial problems. As a consequence, most solvers for the propositional …

Abstract Model checkers and sequential equivalence checkers have become essential tools
for the semiconductor industry in recent years. The Hardware Model Checking Competition …

Unsatisfiability proofs in the DRAT format became the de facto standard to increase the
reliability of contemporary SAT solvers. We consider the problem of generating proofs for the …

Satisfiability testing (SAT) is used to solve many academic and industrial problems from the
complexity class NP, for example hardware verification or scheduling [1]. The described …

Automated configuration is used to improve the performance of a SAT solver. Increasing the
space of possible parameter configurations leverages the power of configuration but also …

One approach to axiom pinpointing (AP) in description logics is its reduction to the
enumeration of minimal unsatisfiable subformulas, allowing for the deployment of highly …

Abstract Conflict Driven Clause Learning (cdcl) SAT solvers spend most of their execution
time iterating through clauses in unit propagation. Efficient implementations of unit …

Unsatisfiability Proofs in SAT Solving with Parity Reasoning Page 1 Unsatisfiability Proofs in
SAT Solving with Parity Reasoning Adrián Rebola-Pardo EMCL Workshop 2016 February 11th …