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The Survey Propagation (SP) algorithm for solving $k$-SAT problems has been shown recently as an instance of the Belief Propagation (BP) algorithm. In this paper, we show that for general constraint-satisfaction problems, SP may not be…

Information Theory · Computer Science 2008-01-31 Ronghui Tu , Yongyi Mao , Jiying Zhao

To address the issue of increased bit error rates during the later stages of linear search in denoising diffusion error correction codes, we propose a novel method that optimizes denoising diffusion error correction codes (ECC) using cosine…

Information Theory · Computer Science 2024-05-07 Congyang Ou , Xiaojing Chen , Wan Jiang

Survey propagation is a powerful technique from statistical physics that has been applied to solve the 3-SAT problem both in principle and in practice. We give, using only probability arguments, a common derivation of survey propagation,…

Statistical Mechanics · Physics 2007-05-23 Erik Aurell , Uri Gordon , Scott Kirkpatrick

Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances and is known to depend strongly on…

Artificial Intelligence · Computer Science 2014-01-07 Holger Hoos , Roland Kaminski , Marius Lindauer , Torsten Schaub

Parallel solving via cube-and-conquer is a key method for scaling SAT solvers to hard instances. While cube-and-conquer has proven successful for pure SAT problems, notably the Pythagorean triples conjecture, its application to SAT solvers…

Artificial Intelligence · Computer Science 2025-01-30 Markus Kirchweger , Hai Xia , Tomáš Peitl , Stefan Szeider

Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation, semidefinite programming relaxations (SDR's) are proposed…

Optimization and Control · Mathematics 2020-03-20 V. Cerone , S. M. Fosson , D. Regruto

Probabilistic graphical models compactly represent joint distributions by decomposing them into factors over subsets of random variables. In Bayesian networks, the factors are conditional probability distributions. For many problems, common…

Machine Learning · Computer Science 2018-08-21 Weirui Kong , Wenyi Wang

Original and learnt clauses in Conflict-Driven Clause Learning (CDCL) SAT solvers often contain redundant literals. This may have a negative impact on performance because redundant literals may deteriorate both the effectiveness of Boolean…

Artificial Intelligence · Computer Science 2018-07-31 Chu-Min Li , Fan Xiao , Mao Luo , Felip Manyà , Zhipeng Lü , Yu Li

This paper introduces the XOR-OR-AND normal form (XNF) for logical formulas. It is a generalization of the well-known Conjunctive Normal Form (CNF) where literals are replaced by XORs of literals. As a first theoretic result, we show that…

Logic in Computer Science · Computer Science 2024-10-25 Bernhard Andraschko , Julian Danner , Martin Kreuzer

As a natural extension of the SAT problem, an array of proof systems for quantified Boolean formulas (QBF) have been proposed, many of which extend a propositional proof system to handle universal quantification. By formalising the…

Logic in Computer Science · Computer Science 2023-06-22 Olaf Beyersdorff , Joshua Blinkhorn , Luke Hinde

Modern quantum annealers can find high-quality solutions to combinatorial optimisation objectives given as quadratic unconstrained binary optimisation (QUBO) problems. Unfortunately, obtaining suitable QUBO forms in computer vision remains…

We consider the problem of finding and enumerating polyominos that can be folded into multiple non-isomorphic boxes. While several computational approaches have been proposed, including SAT, randomized algorithms, and decision diagrams,…

Computational Geometry · Computer Science 2025-06-03 Long Qian , Eric Wang , Bernardo Subercaseaux , Marijn J. H. Heule

Bounded fitting is a general paradigm for learning logical formulas from positive and negative data examples, that has received considerable interest recently. We investigate bounded fitting for the description logic ALC and its syntactic…

Artificial Intelligence · Computer Science 2025-07-30 Maurice Funk , Jean Christoph Jung , Tom Voellmer

Boolean satisfiability is a propositional logic problem of interest in multiple fields, e.g., physics, mathematics, and computer science. Beyond a field of research, instances of the SAT problem, as it is known, require efficient solution…

Emerging Technologies · Computer Science 2020-11-13 S. R. B. Bearden , Y. R. Pei , M. Di Ventra

Constrained optimization problems arise in various engineering systems such as inventory management and power grids. Standard deep neural network (DNN) based machine learning proxies are ineffective in practical settings where labeled data…

Machine Learning · Computer Science 2025-06-09 Parikshit Pareek , Abhijith Jayakumar , Kaarthik Sundar , Deepjyoti Deka , Sidhant Misra

We study the Boolean Satisfiability problem (SAT) in the framework of diversity, where one asks for multiple solutions that are mutually far apart (i.e., sufficiently dissimilar from each other) for a suitable notion of…

Data Structures and Algorithms · Computer Science 2024-12-16 Neeldhara Misra , Harshil Mittal , Ashutosh Rai

Recent research in areas such as SAT solving and Integer Linear Programming has shown that the performances of a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers. We…

Artificial Intelligence · Computer Science 2014-01-07 Roberto Amadini , Maurizio Gabbrielli , Jacopo Mauro

Instances of logical cryptanalysis, circuit verification, and bounded model checking can often be succinctly represented as a combined satisfiability (SAT) problem where an instance is a combination of traditional clauses and parity…

Logic in Computer Science · Computer Science 2012-09-11 Tero Laitinen , Tommi Junttila , Ilkka Niemelä

We propose prioritized unit propagation with periodic resetting, which is a simple but surprisingly effective algorithm for solving random SAT instances that are meant to be hard. In particular, an evaluation on the Random Track of the 2017…

Artificial Intelligence · Computer Science 2019-12-13 Xujie Si , Yujia Li , Vinod Nair , Felix Gimeno

Commonly used proof strategies by automated reasoners organise proof search either by ordering-based saturation or by reducing goals to subgoals. In this paper, we combine these two approaches and advocate a SAT-based method with symmetry…

Logic in Computer Science · Computer Science 2026-03-09 Clemens Eisenhofer , Michael Rawson , Laura Kovács