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Constraint satisfaction problems (CSPs) are about finding values of variables that satisfy the given constraints. We show that Transformer extended with recurrence is a viable approach to learning to solve CSPs in an end-to-end manner,…

Artificial Intelligence · Computer Science 2023-07-12 Zhun Yang , Adam Ishay , Joohyung Lee

In this paper we present a new approach to modeling finite set domain constraint problems using Reduced Ordered Binary Decision Diagrams (ROBDDs). We show that it is possible to construct an efficient set domain propagator which compactly…

Artificial Intelligence · Computer Science 2011-09-13 P. J. Hawkins , V. Lagoon , P. J. Stuckey

This paper presents an approach to the design of autonomous, real-time systems operating in uncertain environments. We address issues of problem solving and reflective control of reasoning under uncertainty in terms of two fundamental…

Artificial Intelligence · Computer Science 2013-04-10 John S. Breese , Michael R. Fehling

A fundamental question that has been studied in cryptography and in information theory is whether two parties can communicate confidentially using exclusively an open channel. We consider the model in which the two parties hold inputs that…

Information Theory · Computer Science 2020-01-10 Marius Zimand

Answer-set programming (ASP) has emerged recently as a viable programming paradigm. We describe here an ASP system, DATALOG with constraints or DC, based on non-monotonic logic. Informally, DC theories consist of propositional clauses…

Artificial Intelligence · Computer Science 2007-05-23 Deborah East , Miroslaw Truszczynski

This paper studies consensus of discrete-time multi-agent systems under time-varying directed communication, state and input constraints using a distributed multi-step model predictive control (MPC) framework. Consensus is recast as…

Optimization and Control · Mathematics 2026-02-18 Navid Noroozi

We study the complexity of constraint satisfaction problems involving global constraints, i.e., special-purpose constraints provided by a solver and represented implicitly by a parametrised algorithm. Such constraints are widely used;…

Artificial Intelligence · Computer Science 2013-07-11 David A. Cohen , Peter G. Jeavons , Evgenij Thorstensen , Stanislav Živný

Many natural combinatorial problems can be expressed as constraint satisfaction problems. This class of problems is known to be NP-complete in general, but certain restrictions on the form of the constraints can ensure tractability. The…

Computational Complexity · Computer Science 2020-10-05 Dmitriy Zhuk

LLM jailbreaks are a widespread safety challenge. Given this problem has not yet been tractable, we suggest targeting a key failure mechanism: the failure of safety to generalize across semantically equivalent inputs. We further focus the…

This paper addresses the problem of giving conditions for transcriptional systems to be globally entrained to external periodic inputs. By using contraction theory, a powerful tool from dynamical systems theory, it is shown that certain…

Quantitative Methods · Quantitative Biology 2015-05-13 Giovanni Russo , Mario di Bernardo , Eduardo D. Sontag

We study the design of one-to-one matching mechanisms that are strategy-proof for both sides and as stable as possible. Motivated by the impossibility result of Roth (1982), we formulate the mechanism design problem as a linear program that…

Theoretical Economics · Economics 2026-02-04 Tohya Sugano

Network security is a growing issue, with the evolution of computer systems and expansion of attacks. Biological systems have been inspiring scientists and designs for new adaptive solutions, such as genetic algorithms. In this paper, we…

Networking and Internet Architecture · Computer Science 2014-03-10 Amira Sayed A. Aziz , Ahmad Taher Azar , Aboul Ella Hassanien , Sanaa Al-Ola Hanafy

This paper introduces an extension of Answer Set Programming called Preference Set Constraint Programming which is a convenient and general formalism to reason with preferences. PSC programming extends Set Constraint Programming introduced…

Logic in Computer Science · Computer Science 2012-03-06 Alex Brik , Jeffrey B. Remmel

We provide here a proof theoretic account of constraint programming that attempts to capture the essential ingredients of this programming style. We exemplify it by presenting proof rules for linear constraints over interval domains, and…

Artificial Intelligence · Computer Science 2007-05-23 Krzysztof R. Apt

In this thesis we explore the benefits of relativistic constraints for cryptography. We first revisit non-communicating models and its applications in the context of interactive proofs and cryptography. We propose bit commitment protocols…

Quantum Physics · Physics 2015-12-03 Jędrzej Kaniewski

Suppose we would like to know all answers to a set of statistical queries C on a data set up to small error, but we can only access the data itself using statistical queries. A trivial solution is to exhaustively ask all queries in C. Can…

Data Structures and Algorithms · Computer Science 2011-10-28 Anupam Gupta , Moritz Hardt , Aaron Roth , Jonathan Ullman

We address combinatorial problems that can be formulated as minimization of a partially separable function of discrete variables (energy minimization in graphical models, weighted constraint satisfaction, pseudo-Boolean optimization, 0-1…

Computer Vision and Pattern Recognition · Computer Science 2015-05-05 Alexander Shekhovtsov

We propose finitely convergent methods for solving convex feasibility problems defined over a possibly infinite pool of constraints. Following other works in this area, we assume that the interior of the solution set is nonempty and that…

Optimization and Control · Mathematics 2020-09-22 Victor I. Kolobov , Simeon Reich , Rafał Zalas

It is known that the composition of schema mappings, each specified by source-to-target tgds (st-tgds), can be specified by a second-order tgd (SO tgd). We consider the question of what happens when target constraints are allowed.…

Databases · Computer Science 2015-07-01 Marcelo Arenas , Ronald Fagin , Alan Nash

In safety-critical machine learning applications, it is crucial to defend models against adversarial attacks -- small modifications of the input that change the predictions. Besides rigorously studied $\ell_p$-bounded additive…

Machine Learning · Computer Science 2022-08-16 Mikhail Pautov , Nurislam Tursynbek , Marina Munkhoeva , Nikita Muravev , Aleksandr Petiushko , Ivan Oseledets