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Lightweight axiom pinpointing via replicated driver and customized SAT-solving
In description logic, axiom pinpointing is used to explore defects in ontologies and identify hidden justifications for a logical consequence. In...
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Reasoning and inference for (Maximum) satisfiability: new insights
At the heart of computer science and artificial intelligence, logic is often used as a powerful language to model and solve complex problems that...
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Learning Variable Activity Initialisation for Lazy Clause Generation Solvers
Contemporary research explores the possibilities of integrating machine learning (ML) approaches with traditional combinatorial optimisation solvers....
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UNSAT Solver Synthesis via Monte Carlo Forest Search
We introduce Monte Carlo Forest Search (MCFS), a class of reinforcement learning (RL) algorithms for learning policies in tree MDPs, for which policy...
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Domain Dependent Parameter Setting in SAT Solver Using Machine Learning Techniques
We address the problem of variable and truth-value choice in modern search-based Boolean satisfiability (SAT) solvers depending on the problem...
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Diversification of Parallel Search of Portfolio SAT Solver by Search Similarity Index
Parallelization is essential for the acceleration of SAT solvers, and for this purpose, the portfolio approach is a key technique. As the diversity...
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Towards a Complexity-Theoretic Understanding of Restarts in SAT Solvers
Restarts are a widely-used class of techniques integral to the efficiency of Conflict-Driven Clause Learning (CDCL) Boolean SAT solvers. While the...
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SMT solving for the validation of B and Event-B models
ProB provides a constraint solver for the B-method written in Prolog and can make use of different backends based on SAT and SMT solving. One such...
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A branching heuristic for SAT solvers based on complete implication graphs
The performance of modern conflict-driven clause learning (CDCL) SAT solvers strongly depends on branching heuristics. State-of-the-art branching...
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On Dedicated CDCL Strategies for PB Solvers
Current implementations of pseudo-Boolean (PB) solvers working on native PB constraints are based on the CDCL architecture which empowers highly...
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Deep Cooperation of CDCL and Local Search for SAT
Modern SAT solvers are based on a paradigm named conflict driven clause learning (CDCL), while local search is an important alternative. Although...
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Heavy Weighting for Potential Important Clauses
The Partial Maximum Satisfiability Problem (PMS) is an optimization variant of the satisfiability problem. It involves separating constraints into...
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Exploiting Similarity in Evolutionary Product Design for Improved Design Space Exploration
The design of new products is often an evolutionary process, where product versions are built on one another. This form of (PGE) reuses some parts of...
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A More Pragmatic CDCL for IsaSAT and Targetting LLVM (Short Paper)
IsaSAT is the most advanced verified SAT solver, but it did not yet feature inprocessing (to simplify and strengthen clauses). In order to improve...
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Assessing Progress in SAT Solvers Through the Lens of Incremental SAT
There is a wide consensus, which is supported by the hard experimental evidence of the SAT competitions, that clear progress in SAT solver...
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The MergeSat Solver
Successful SAT solvers in recent competitions are typically based on the winner of the previous competition. Due to this procedure, for multiple...
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Improving Implementation of SAT Competitions 2017–2019 Winners
The results of annual SAT competitions are often viewed as the milestones showcasing the progress in SAT solvers. However, their competitive nature...
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Dagster: Parallel Structured Search with Case Studies
We describe Dagster, a system that implements a new approach to scheduling interdependent (Boolean) SAT search activities in high-performance...
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Searching for i-Good Lemmas to Accelerate Safety Model Checking
IC3/PDR and its variants have been the prominent approaches to safety model checking in recent years. Compared to the previous model-checking...