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The paper suggests the use of Multi-Valued Decision Diagrams (MDDs) as the supporting data structure for a generic global constraint. We give an algorithm for maintaining generalized arc consistency (GAC) on this constraint that amortizes…

Artificial Intelligence · Computer Science 2007-05-23 Peter Tiedemann , Henrik Reif Andersen , Rasmus Pagh

In this paper, we introduce a set of tools for providing user-friendly explanations in an explanation-based constraint programming system. The idea is to represent the constraints of a problem as an hierarchy (a tree). Users are then…

Programming Languages · Computer Science 2007-05-23 Narendra Jussien , Samir Ouis

Automated theorem provers and formal proof assistants are general reasoning systems that are in theory capable of proving arbitrarily hard theorems, thus solving arbitrary problems reducible to mathematics and logical reasoning. In…

Artificial Intelligence · Computer Science 2025-06-23 Lasse Blaauwbroek , David Cerna , Thibault Gauthier , Jan Jakubův , Cezary Kaliszyk , Martin Suda , Josef Urban

In most constraint programming systems, a limited number of search engines is offered while the programming of user-customized search algorithms requires low-level efforts, which complicates the deployment of such algorithms. To alleviate…

Programming Languages · Computer Science 2016-02-05 Yong Lin , Martin Henz

Fragment-based shape signature techniques have proven to be powerful tools for computer-aided drug design. They allow scientists to search for target molecules with some similarity to a known active compound. They do not require reference…

Artificial Intelligence · Computer Science 2022-01-05 Thierry Petit , Randy J. Zauhar

To solve hard problems, AI relies on a variety of disciplines such as logic, probabilistic reasoning, machine learning and mathematical programming. Although it is widely accepted that solving real-world problems requires an integration…

Artificial Intelligence · Computer Science 2020-01-14 Vaishak Belle , Luc De Raedt

We develop combinatorial test generation algorithms for progressively more powerful theorem provers, covering formula languages ranging from the implicational fragment of intuitionistic logic to full intuitionistic propositional logic. Our…

Logic in Computer Science · Computer Science 2019-10-07 Paul Tarau

We revisit the concept of constraint embedding as a means for dealing with kinematic loop constraints during dynamics computations for rigid-body systems. Specifically, we consider the local loop constraints emerging from common actuation…

Robotics · Computer Science 2024-10-24 Matthew Chignoli , Nicholas Adrian , Sangbae Kim , Patrick M. Wensing

We propose new filtering algorithms for the SEQUENCE constraint and some extensions of the SEQUENCE constraint based on network flows. We enforce domain consistency on the SEQUENCE constraint in $O(n^2)$ time down a branch of the search…

Artificial Intelligence · Computer Science 2009-09-25 Michael J. Maher , Nina Narodytska , Claude-Guy Quimper , Toby Walsh

Constraint programming can definitely be seen as a model-driven paradigm. The users write programs for modeling problems. These programs are mapped to executable models to calculate the solutions. This paper focuses on efficient model…

Artificial Intelligence · Computer Science 2010-02-16 Raphael Chenouard , Laurent Granvilliers , Ricardo Soto

In this paper, we are concerned with geometric constraint solvers, i.e., with programs that find one or more solutions of a geometric constraint problem. If no solution exists, the solver is expected to announce that no solution has been…

Graphics · Computer Science 2017-01-09 Ioannis Fudos , Christoph M. Hoffmann , Robert Joan-Arinyo

This paper introduces an approach to endow generative diffusion processes the ability to satisfy and certify compliance with constraints and physical principles. The proposed method recast the traditional sampling process of generative…

Machine Learning · Computer Science 2024-11-05 Jacob K Christopher , Stephen Baek , Ferdinando Fioretto

We propose a method for inferring \emph{parameterized regular types} for logic programs as solutions for systems of constraints over sets of finite ground Herbrand terms (set constraint systems). Such parameterized regular types generalize…

Logic in Computer Science · Computer Science 2010-02-16 F. Bueno , J. Navas , M. Hermenegildo

Causal discovery studies the problem of mining causal relationships between variables from data, which is of primary interest in science. During the past decades, significant amount of progresses have been made toward this fundamental data…

Artificial Intelligence · Computer Science 2016-11-28 Kui Yu , Jiuyong Li , Lin Liu

Consensus is an often occurring problem in concurrent and distributed programming. We present a programming language with simple semantics and build-in support for consensus in the form of communicating transactions. We motivate the need…

Programming Languages · Computer Science 2013-05-08 Carlo Spaccasassi , Vasileios Koutavas

Discovering pattern sets or global patterns is an attractive issue from the pattern mining community in order to provide useful information. By combining local patterns satisfying a joint meaning, this approach produces patterns of higher…

Machine Learning · Computer Science 2011-07-19 Patrice Boizumault , Bruno Crémilleux , Mehdi Khiari , Samir Loudni , Jean-Philippe Métivier

Algorithms often have tunable parameters that impact performance metrics such as runtime and solution quality. For many algorithms used in practice, no parameter settings admit meaningful worst-case bounds, so the parameters are made…

Machine Learning · Computer Science 2021-04-27 Maria-Florina Balcan , Dan DeBlasio , Travis Dick , Carl Kingsford , Tuomas Sandholm , Ellen Vitercik

Parity constraints, common in application domains such as circuit verification, bounded model checking, and logical cryptanalysis, are not necessarily most efficiently solved if translated into conjunctive normal form. Thus, specialized…

Logic in Computer Science · Computer Science 2014-06-19 Tero Laitinen , Tommi Junttila , Ilkka Niemelä

When implementing a propagator for a constraint, one must decide about variants: When implementing min, should one also implement max? Should one implement linear constraints both with unit and non-unit coefficients? Constraint variants are…

Artificial Intelligence · Computer Science 2009-08-17 Christian Schulte , Guido Tack

The paper demonstrates that strict adherence to probability theory does not preclude the use of concurrent, self-activated constraint-propagation mechanisms for managing uncertainty. Maintaining local records of sources-of-belief allows…

Artificial Intelligence · Computer Science 2013-04-15 Judea Pearl
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