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The complete reason behind a decision is a Boolean formula that characterizes why the decision was made. This recently introduced notion has a number of applications, which include generating explanations, detecting decision bias and…

Artificial Intelligence · Computer Science 2022-03-22 Adnan Darwiche , Chunxi Ji

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

We prove the #P-hardness of the counting problems associated with various satisfiability, graph and combinatorial problems, when restricted to planar instances. These problems include \begin{romannum} \item[{}] {\sc 3Sat, 1-3Sat, 1-Ex3Sat,…

Computational Complexity · Computer Science 2007-05-23 Harry B. Hunt , Madhav V. Marathe , Venkatesh Radhakrishnan , Richard E. Stearns

Compositional generalization is a crucial property in artificial intelligence, enabling models to handle novel combinations of known components. While most deep learning models lack this capability, certain models succeed in specific tasks,…

Machine Learning · Computer Science 2025-05-06 Yuanpeng Li

The boolean satisfiability (SAT) problem asks whether there exists an assignment of boolean values to the variables of an arbitrary boolean formula making the formula evaluate to True. It is well-known that all NP-problems can be coded as…

Machine Learning · Computer Science 2024-10-22 Christopher R. Serrano , Jonathan Gallagher , Kenji Yamada , Alexei Kopylov , Michael A. Warren

Any satisfiability problem in conjunctive normal form can be solved in polynomial time by reducing it to a 3-sat formulation and transforming this to a Linear Complementarity problem (LCP) which is then solved as a linear program (LP). Any…

Computational Complexity · Computer Science 2018-01-31 Giacomo Patrizi

We develop a complexity theory for approximate real computations. We first produce a theory for exact computations but with condition numbers. The input size depends on a condition number, which is not assumed known by the machine. The…

Computational Complexity · Computer Science 2020-05-05 Gregorio Malajovich , Mike Shub

In this paper we present a new approach to solve the satisfiability problem (SAT), based on boolean networks (BN). We define a mapping between a SAT instance and a BN, and we solve SAT problem by simulating the BN dynamics. We prove that BN…

Artificial Intelligence · Computer Science 2011-02-01 Andrea Roli , Michela Milano

We derive novel conditions that guarantee convergence of the Sum-Product algorithm (also known as Loopy Belief Propagation or simply Belief Propagation) to a unique fixed point, irrespective of the initial messages. The computational…

Information Theory · Computer Science 2007-12-18 Joris M. Mooij , Hilbert J. Kappen

Logical models have been successfully used to describe regulatory and signaling networks without requiring quantitative data. However, existing data is insufficient to adequately define a unique model, rendering the parametrization of a…

Discrete Mathematics · Computer Science 2019-01-24 José E. R. Cury , Pedro T. Monteiro , Claudine Chaouiya

We establish a lower bound for deciding the satisfiability of the conjunction of any two Boolean formulas from a set called a full representation of Boolean functions of $n$ variables - a set containing a Boolean formula to represent each…

Computational Complexity · Computer Science 2014-06-24 Samuel C. Hsieh

We introduce the problem of temporal coverability for realizability and synthesis. Namely, given a language of words that must be covered by a produced system, how to automatically produce such a system. We consider the case of coverability…

Logic in Computer Science · Computer Science 2018-04-11 Krishnendu Chatterjee , Nir Piterman

This is the first of three planned papers describing ZAP, a satisfiability engine that substantially generalizes existing tools while retaining the performance characteristics of modern high-performance solvers. The fundamental idea…

Artificial Intelligence · Computer Science 2011-07-04 H. E. Dixon , M. L. Ginsberg , A. J. Parkes

As complex machine learning models continue to find applications in high-stakes decision-making scenarios, it is crucial that we can explain and understand their predictions. Post-hoc explanation methods provide useful insights by…

Machine Learning · Statistics 2024-10-16 Beepul Bharti , Paul Yi , Jeremias Sulam

Typestate systems ensure many desirable properties of imperative programs, including initialization of object fields and correct use of stateful library interfaces. Abstract sets with cardinality constraints naturally generalize typestate…

Programming Languages · Computer Science 2013-02-14 Bruno Marnette , Viktor Kuncak , Martin Rinard

A workflow specification defines a set of steps and the order in which those steps must be executed. Security requirements may impose constraints on which groups of users are permitted to perform subsets of those steps. A workflow…

Cryptography and Security · Computer Science 2013-01-10 Jason Crampton , Gregory Gutin , Anders Yeo

This paper presents a complete algorithmic study of the decision Boolean Satisfiability Problem under the classical computation and quantum computation theories. The paper depicts deterministic and probabilistic algorithms, propositions of…

Computational Complexity · Computer Science 2016-02-22 Carlos Barrón-Romero

This is the report-version of a mini-series of two articles on the foundations of satisfiability of conjunctive normal forms with non-boolean variables, to appear in Fundamenta Informaticae, 2011. These two parts are here bundled in one…

Discrete Mathematics · Computer Science 2012-02-15 Oliver Kullmann

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

Understanding the behavior of learned classifiers is an important task, and various black-box explanations, logical reasoning approaches, and model-specific methods have been proposed. In this paper, we introduce probabilistic sufficient…

Machine Learning · Computer Science 2021-05-24 Eric Wang , Pasha Khosravi , Guy Van den Broeck