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Transforming constraint models is an important task in re- cent constraint programming systems. User-understandable models are defined during the modeling phase but rewriting or tuning them is manda- tory to get solving-efficient models. We…

Artificial Intelligence · Computer Science 2010-02-17 Raphael Chenouard , Laurent Granvilliers , Ricardo Soto

We present a new approach to enhancing Answer Set Programming (ASP) with Constraint Processing techniques which allows for solving interesting Constraint Satisfaction Problems in ASP. We show how constraints on finite domains can be…

Logic in Computer Science · Computer Science 2010-07-26 Christian Drescher , Toby Walsh

Model reduction, which aims to learn a simpler model of the original mixed integer linear programming (MILP), can solve large-scale MILP problems much faster. Most existing model reduction methods are based on variable reduction, which…

Machine Learning · Computer Science 2026-02-04 Jiajun Li , Yixuan Li , Ran Hou , Yu Ding , Shisi Guan , Jiahui Duan , Xiongwei Han , Tao Zhong , Vincent Chau , Weiwei Wu , Wanyuan Wang

In this paper we accomplish the development of the fast rank-adaptive solver for tensor-structured symmetric positive definite linear systems in higher dimensions. In [arXiv:1301.6068] this problem is approached by alternating minimization…

Numerical Analysis · Mathematics 2014-10-07 Sergey V. Dolgov , Dmitry V. Savostyanov

Constraint problems can be trivially solved in parallel by exploring different branches of the search tree concurrently. Previous approaches have focused on implementing this functionality in the solver, more or less transparently to the…

Artificial Intelligence · Computer Science 2010-08-26 Lars Kotthoff , Neil C. A. Moore

Modeling symmetry breaking is essential for understanding the fundamental changes in the behaviors and properties of physical systems, from microscopic particle interactions to macroscopic phenomena like fluid dynamics and cosmic…

Machine Learning · Computer Science 2025-07-11 Rui Wang , Elyssa Hofgard , Han Gao , Robin Walters , Tess E. Smidt

Symmetry can be used to help solve many problems. For instance, Einstein's famous 1905 paper ("On the Electrodynamics of Moving Bodies") uses symmetry to help derive the laws of special relativity. In artificial intelligence, symmetry has…

Artificial Intelligence · Computer Science 2010-07-06 Toby Walsh

Symmetry breaking is a popular technique to reduce the search space for SAT solving by exploiting the underlying symmetry over variables and clauses in a formula. The key idea is to first identify sets of assignments which fall in the same…

Logic in Computer Science · Computer Science 2020-01-17 Saket Dingliwal , Ronak Agarwal , Happy Mittal , Parag Singla

Symmetry is an important factor in solving many constraint satisfaction problems. One common type of symmetry is when we have symmetric values. In a recent series of papers, we have studied methods to break value symmetries. Our results…

Artificial Intelligence · Computer Science 2009-03-04 Toby Walsh

Symmetry in mathematical programming may lead to a multiplicity of solutions. In nonconvex optimisation, it can negatively affect the performance of the branch-and-bound algorithm. Symmetry may induce large search trees with multiple…

Optimization and Control · Mathematics 2019-01-23 Georgia Kouyialis , Ruth Misener

This paper introduces the concept of abstracted model reduction: a framework to improve the tractability of structure-preserving methods for the complexity reduction of interconnected system models. To effectively reduce high-order,…

Systems and Control · Electrical Eng. & Systems 2024-11-21 Luuk Poort , Lars A. L. Janssen , Bart Besselink , Rob H. B. Fey , Nathan van de Wouw

Code optimization and high level synthesis can be posed as constraint satisfaction and optimization problems, such as graph coloring used in register allocation. Graph coloring is also used to model more traditional CSPs relevant to AI,…

Artificial Intelligence · Computer Science 2011-09-13 F. A. Aloul , I. L. Markov , A. Ramani , K. A. Sakallah

Equivariant neural networks (ENNs) have been shown to be extremely effective in applications involving underlying symmetries. By construction ENNs cannot produce lower symmetry outputs given a higher symmetry input. However, symmetry…

Machine Learning · Computer Science 2024-11-15 YuQing Xie , Tess Smidt

Symmetries are intrinsic to many combinatorial problems including Boolean Satisfiability (SAT) and Constraint Programming (CP). In SAT, the identification of symmetry breaking predicates (SBPs) is a well-known, often effective, technique…

Artificial Intelligence · Computer Science 2008-12-18 Joao Marques-Silva , Ines Lynce , Vasco Manquinho

Symmetry in integer programming causes redundant search and is often handled with symmetry breaking constraints that remove as many equivalent solutions as possible. We propose an algebraic method which allows to generate a random family of…

Symbolic Computation · Computer Science 2026-02-10 Madalina Erascu , Johannes Middeke

Static program analysis is a valuable tool for any programming language that people write programs in. The prevalence of scripting languages in the world suggests programming language interpreters are relatively easy to write. Users of…

Programming Languages · Computer Science 2015-05-01 James Ian Johnson

Symmetries in discrete constraint satisfaction problems have been explored and exploited in the last years, but symmetries in continuous constraint problems have not received the same attention. Here we focus on permutations of the…

Artificial Intelligence · Computer Science 2014-01-16 Vicente Ruiz de Angulo , Carme Torras

Symmetry reduction is crucial for solving many interesting SAT instances in practice. Numerous approaches have been proposed, which try to strike a balance between symmetry reduction and computational overhead. Arguably the most readily…

Data Structures and Algorithms · Computer Science 2024-06-21 Markus Anders , Sofia Brenner , Gaurav Rattan

In the talk at the workshop my aim was to demonstrate the usefulness of graph techniques for tackling problems that have been studied predominantly as problems on the term level: increasing sharing in functional programs, and addressing…

Logic in Computer Science · Computer Science 2019-02-07 Clemens Grabmayer

Constraint programming (CP) is a powerful tool for modeling mathematical concepts and objects and finding both solutions or counter examples. One of the major strengths of CP is that problems can easily be combined or expanded. In this…

Discrete Mathematics · Computer Science 2025-01-29 Ruth Hoffmann , Özgür Akgün , Christopher Jefferson