The silent (r) evolution of SAT
The Silent (R)evolution of SAT Page 1 THE PROPOSITIONAL SATISFIABILITY problem (SAT)
was the first to be shown NP-complete by Cook and Levin. SAT remained the embodiment of …
was the first to be shown NP-complete by Cook and Levin. SAT remained the embodiment of …
[PDF][PDF] Integrating tree decompositions into decision heuristics of propositional model counters
T Korhonen, M Järvisalo - 27th International Conference …, 2021 - researchportal.helsinki.fi
Abstract Propositional model counting (# SAT), the problem of determining the number of
satisfying assignments of a propositional formula, is the archetypical# P-complete problem …
satisfying assignments of a propositional formula, is the archetypical# P-complete problem …
Tseitin or not tseitin? the impact of cnf transformations on feature-model analyses
Feature modeling is widely used to systematically model features of variant-rich software
systems and their dependencies. By translating feature models into propositional formulas …
systems and their dependencies. By translating feature models into propositional formulas …
Evaluating state-of-the-art # SAT solvers on industrial configuration spaces
Product lines are widely used to manage families of products that share a common base of
features. Typically, not every combination (configuration) of features is valid. Feature models …
features. Typically, not every combination (configuration) of features is valid. Feature models …
Treewidth-aware reductions of normal ASP to SAT–Is normal ASP harder than SAT after all?
M Hecher - Artificial Intelligence, 2022 - Elsevier
Abstract Answer Set Programming (ASP) is a paradigm for modeling and solving problems
for knowledge representation and reasoning. There are plenty of results dedicated to …
for knowledge representation and reasoning. There are plenty of results dedicated to …
Rushing and strolling among answer sets–navigation made easy
Answer set programming (ASP) is a popular declarative programming paradigm with a wide
range of applications in artificial intelligence. Oftentimes, when modeling an AI problem with …
range of applications in artificial intelligence. Oftentimes, when modeling an AI problem with …
Rounding meets approximate model counting
The problem of model counting, also known as, is to compute the number of models or
satisfying assignments of a given Boolean formula F. Model counting is a fundamental …
satisfying assignments of a given Boolean formula F. Model counting is a fundamental …
Exploiting database management systems and treewidth for counting
Bounded treewidth is one of the most cited combinatorial invariants in the literature. It was
also applied for solving several counting problems efficiently. A canonical counting problem …
also applied for solving several counting problems efficiently. A canonical counting problem …
[PDF][PDF] Plausibility Reasoning via Projected Answer Set Counting-A Hybrid Approach.
Answer set programming is a form of declarative programming widely used to solve difficult
search problems. Probabilistic applications however require to go beyond simple search for …
search problems. Probabilistic applications however require to go beyond simple search for …
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
Propositional satisfiability (SAT) is an NP-complete problem that impacts many research
fields, such as planning, verification, and security. Mainstream modern SAT solvers are …
fields, such as planning, verification, and security. Mainstream modern SAT solvers are …