English
Related papers

Related papers: Exploring the Use of Shatter for AllSAT Through Ra…

200 papers

The 3-Satisfiability Problem (3-SAT) is a demanding combinatorial problem, of central importance among the non-deterministic polynomial (NP) complete problems, with applications in circuit design, artificial intelligence and logistics. Even…

Symmetry breaking has been proven to be an efficient preprocessing technique for satisfiability solving (SAT). In this paper, we port the state-of-the-art SAT symmetry breaker BreakID to answer set programming (ASP). The result is a…

Artificial Intelligence · Computer Science 2016-08-31 Jo Devriendt , Bart Bogaerts

Graph generation and enumeration problems often require handling equivalent graphs -- those that differ only in vertex labeling. We study how to extend SAT Modulo Symmetries (SMS), a framework for eliminating such redundant graphs, to…

Logic in Computer Science · Computer Science 2025-02-24 Mikoláš Janota , Markus Kirchweger , Tomáš Peitl , Stefan Szeider

Ramsey theory looks for regularities in large objects. Model theory studies algebraic structures as models of theories. The structural Ramsey theory combines these two fields and is concerned with Ramsey-type questions about certain…

Combinatorics · Mathematics 2018-05-22 Matěj Konečný

Architectures for quantum computing based on neutral atoms have risen to prominence as candidates for both near and long-term applications. These devices are particularly well suited to solve independent set problems, as the combinatorial…

It was shown before that the NP-hard problem of deterministic finite automata (DFA) identification can be effectively translated to Boolean satisfiability (SAT). Modern SAT-solvers can tackle hard DFA identification instances efficiently.…

Formal Languages and Automata Theory · Computer Science 2016-02-22 Vladimir Ulyantsev , Ilya Zakirzyanov , Anatoly Shalyto

In practice symmetries of combinatorial structures are computed by transforming the structure into an annotated graph whose automorphisms correspond exactly to the desired symmetries. An automorphism solver is then employed to compute the…

Data Structures and Algorithms · Computer Science 2021-08-11 Markus Anders , Pascal Schweitzer

Given a CNF formula F on n variables, the problem of model counting or #SAT is to compute the number of satisfying assignments of F . Model counting is a fundamental but hard problem in computer science with varied applications. Recent…

Data Structures and Algorithms · Computer Science 2020-05-01 Kuldeep S. Meel , S. Akshay

In many decision-making processes, one may prefer multiple solutions to a single solution, which allows us to choose an appropriate solution from the set of promising solutions that are found by algorithms. Given this, finding a set of…

Data Structures and Algorithms · Computer Science 2024-12-06 Tatsuya Gima , Yuni Iwamasa , Yasuaki Kobayashi , Kazuhiro Kurita , Yota Otachi , Rin Saito

Algebraic Normal Form (ANF) and Conjunctive Normal Form (CNF) are commonly used to encode problems in Boolean algebra. ANFs are typically solved via Gr"obner basis algorithms, often using more memory than is feasible; while CNFs are solved…

Logic in Computer Science · Computer Science 2018-12-19 Davin Choo , Mate Soos , Kian Ming A. Chai , Kuldeep S. Meel

The poset cover problem seeks a minimum set of partial orders whose linear extensions cover a given set of linear orders. Recognizing its NP-completeness, we devised a non-trivial reduction to the Boolean satisfiability problem using a…

Logic in Computer Science · Computer Science 2025-05-08 Chih-Cheng Rex Yuan , Bow-Yaw Wang

Matrix concentration inequalities and their recently discovered sharp counterparts provide powerful tools to bound the spectrum of random matrices whose entries are linear functions of independent random variables. However, in many…

Probability · Mathematics 2025-04-02 Afonso S. Bandeira , Kevin Lucca , Petar Nizić-Nikolac , Ramon van Handel

Graph neural networks (GNNs) have pushed the state-of-the-art (SOTA) for performance in learning and predicting on large-scale data present in social networks, biology, etc. Since integrated circuits (ICs) can naturally be represented as…

Machine Learning · Computer Science 2022-11-30 Lilas Alrahis , Johann Knechtel , Ozgur Sinanoglu

Irregular computations on unstructured data are an important class of problems for parallel programming. Graph coloring is often an important preprocessing step, e.g. as a way to perform dependency analysis for safe parallel execution. The…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-19 Georgios Rokos , Gerard Gorman , Paul H J Kelly

We study creating and analyzing symmetry and broken symmetry in digital art. Our focus is not so much on computer-generating artistic images, but rather on analyzing concepts and templates for incorporating symmetry and symmetry breaking…

Neural and Evolutionary Computing · Computer Science 2019-10-16 Hendrik Richter

Representing patterns as labeled graphs is becoming increasingly common in the broad field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools, such as classifiers and knowledge discovery procedures,…

Computer Vision and Pattern Recognition · Computer Science 2017-05-11 Lorenzo Livi

In this paper we prove a new result about partitioning coloured complete graphs and use it to determine certain Ramsey numbers exactly. The partitioning theorem we prove is that for k at least 1, in every edge colouring of a complete graph…

Combinatorics · Mathematics 2013-09-17 Alexey Pokrovskiy

We present a new algorithm for determining the satisfiability of conjunctions of non-linear polynomial constraints over the reals, which can be used as a theory solver for satisfiability modulo theory (SMT) solving for non-linear real…

Symbolic Computation · Computer Science 2021-06-17 Erika Ábrahám , James H. Davenport , Matthew England , Gereon Kremer

Scatterplot selection is an effective approach to represent essential portions of multidimensional data in a limited display space. Various metrics for evaluation of scatterplots such as scagnostics have been presented and applied to…

Human-Computer Interaction · Computer Science 2020-09-17 Takayuki Itoh , Asuka Nakabayashi , Mariko Hagita

In Machine Learning, the $\mathsf{SHAP}$-score is a version of the Shapley value that is used to explain the result of a learned model on a specific entity by assigning a score to every feature. While in general computing Shapley values is…

Artificial Intelligence · Computer Science 2023-03-31 Marcelo Arenas , Pablo Barceló , Leopoldo Bertossi , Mikaël Monet