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相关论文: A Logical Approach to Efficient Max-SAT solving

200 篇论文

Given a boolean formula $\Phi$(X, Y, Z), the Max\#SAT problem asks for finding a partial model on the set of variables X, maximizing its number of projected models over the set of variables Y. We investigate a strict generalization of…

密码学与安全 · 计算机科学 2023-09-13 Thomas Vigouroux , Marius Bozga , Cristian Ene , Laurent Mounier

Reconfiguration aims at recovering a system from a fault by automatically adapting the system configuration, such that the system goal can be reached again. Classical approaches typically use a set of pre-defined faults for which…

人工智能 · 计算机科学 2021-05-19 Kaja Balzereit , Oliver Niggemann

The class PLS (Polynomial Local Search) captures the complexity of finding a solution that is locally optimal and has proven to be an important concept in the theory of local search. It has been shown that local search versions of various…

数据结构与算法 · 计算机科学 2025-12-16 Yasuaki Kobayashi , Kazuhiro Kurita , Yutaro Yamaguchi

Many natural optimization problems are NP-hard, which implies that they are probably hard to solve exactly in the worst-case. However, it suffices to get reasonably good solutions for all (or even most) instances in practice. This paper…

人工智能 · 计算机科学 2022-09-13 Raffaele Marino

The practical success of Boolean Satisfiability (SAT) solvers stems from the CDCL (Conflict-Driven Clause Learning) approach to SAT solving. However, from a propositional proof complexity perspective, CDCL is no more powerful than the…

计算机科学中的逻辑 · 计算机科学 2017-07-06 Alexey Ignatiev , Antonio Morgado , Joao Marques-Silva

Satisfiability-based verification techniques, leveraging modern Boolean satisfiability (SAT) and Satisfiability Modulo Theories (SMT) solvers, have demonstrated efficacy in addressing practical problem instances within program analysis.…

计算机科学中的逻辑 · 计算机科学 2025-09-23 Markus Krahl , Matthias Güdemann , Stefan Wallentowitz

As a natural variant of the $k$-SAT problem, NAE-$k$-SAT additionally requires the literals in each clause to take not-all-equal (NAE) truth values. In this paper, we study the worst-case time complexities of solving NAE-$k$-SAT and…

计算复杂性 · 计算机科学 2019-06-27 S. Cliff Liu

The most successful parallel SAT and MaxSAT solvers follow a portfolio approach, where each thread applies a different algorithm (or the same algorithm configured differently) to solve a given problem instance. The main goal of building a…

计算机科学中的逻辑 · 计算机科学 2015-05-12 Miguel Neves , Inês Lynce , Vasco Manquinho

We explore the potential of continuous local search (CLS) in SAT solving by proposing a novel approach for finding a solution of a hybrid system of Boolean constraints. The algorithm is based on CLS combined with belief propagation on…

人工智能 · 计算机科学 2021-06-15 Anastasios Kyrillidis , Moshe Y. Vardi , Zhiwei Zhang

Max-norm regularizer has been extensively studied in the last decade as it promotes an effective low-rank estimation for the underlying data. However, such max-norm regularized problems are typically formulated and solved in a batch manner,…

机器学习 · 统计学 2016-05-17 Jie Shen , Huan Xu , Ping Li

There are a huge number of problems, from various areas, being solved by reducing them to SAT. However, for many applications, translation into SAT is performed by specialized, problem-specific tools. In this paper we describe a new system…

人工智能 · 计算机科学 2015-07-01 Predrag Janicic

Though numerous solvers have been proposed for the MaxSAT problem, and the benchmark environment such as MaxSAT Evaluations provides a platform for the comparison of the state-of-the-art solvers, existing assessments were usually evaluated…

人工智能 · 计算机科学 2026-04-09 Furong Ye , Chuan Luo , Shaowei Cai

This paper reviews the recent literature on solving the Boolean satisfiability problem (SAT), an archetypal NP-complete problem, with the help of machine learning techniques. Despite the great success of modern SAT solvers to solve large…

人工智能 · 计算机科学 2023-10-25 Wenxuan Guo , Junchi Yan , Hui-Ling Zhen , Xijun Li , Mingxuan Yuan , Yaohui Jin

The computational complexity of solving random 3-Satisfiability (3-SAT) problems is investigated. 3-SAT is a representative example of hard computational tasks; it consists in knowing whether a set of alpha N randomly drawn logical…

统计力学 · 物理学 2009-10-31 Simona Cocco , Remi Monasson

Since the amount of information on the internet is growing rapidly, it is not easy for a user to find relevant information for his/her query. To tackle this issue, much attention has been paid to Automatic Document Summarization. The key…

计算与语言 · 计算机科学 2019-02-05 Kamal Al-Sabahi , Zhang Zuping , Yang Kang

Due to the wide employment of automated reasoning in the analysis and construction of correct systems, the results reported by automated reasoning engines must be trustworthy. For Boolean satisfiability (SAT) solvers - and more recently…

人工智能 · 计算机科学 2025-05-22 Christoph Jabs , Jeremias Berg , Bart Bogaerts , Matti Järvisalo

Recently, Xu and Zhou [2023] introduced a constructive approach for exploring computational hardness, proving that SAT requires exhaustive search. In light of certain misinterpretations concerning the contributions and proofs in that paper,…

计算复杂性 · 计算机科学 2024-01-18 Qingxiu Dong , Guangyan Zhou , Ke Xu

This paper presents an algorithm for 3-SAT problems. First, logical formulas are transformed into elementary algebraic formulas. Second, complex trigonometric functions are assigned to the variables in the elementary algebraic formulas, and…

数据结构与算法 · 计算机科学 2017-08-01 Hiroshi Tsukimoto

The Boolean matrix factorization problem consists in approximating a matrix by the Boolean product of two smaller Boolean matrices. To obtain optimal solutions when the matrices to be factorized are small, we propose SAT and MaxSAT…

机器学习 · 计算机科学 2021-06-21 Florent Avellaneda , Roger Villemaire

We introduce SATBench, a benchmark for evaluating the logical reasoning capabilities of large language models (LLMs) through logical puzzles derived from Boolean satisfiability (SAT) problems. Unlike prior work that focuses on inference…

人工智能 · 计算机科学 2025-09-23 Anjiang Wei , Yuheng Wu , Yingjia Wan , Tarun Suresh , Huanmi Tan , Zhanke Zhou , Sanmi Koyejo , Ke Wang , Alex Aiken