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We establish a linear programming formulation for the solution of joint chance constrained optimal control problems over finite time horizons. The joint chance constraint may represent an invariance, reachability or reach-avoid…

Optimization and Control · Mathematics 2024-05-21 Niklas Schmid , Marta Fochesato , Tobias Sutter , John Lygeros

We consider a class of linear programs on graphs with total variation regularization and a budgetary constraint. For these programs, we give a characterization of basic solutions in terms of rooted spanning forests with orientation on the…

Optimization and Control · Mathematics 2026-05-20 Dominic Yang

We present a comprehensive programme analysing the decomposition of proof systems for non-classical logics into proof systems for other logics, especially classical logic, using an algebra of constraints. That is, one recovers a proof…

Logic in Computer Science · Computer Science 2023-10-20 Alexander V. Gheorghiu , David J. Pym

Commutativity has proven to be a powerful tool in reasoning about concurrent programs. Recent work has shown that a commutativity-based reduction of a program may admit simpler proofs than the program itself. The framework of…

Programming Languages · Computer Science 2023-11-07 Azadeh Farzan , Dominik Klumpp , Andreas Podelski

Constraint propagation is one of the basic forms of inference in many logic-based reasoning systems. In this paper, we investigate constraint propagation for first-order logic (FO), a suitable language to express a wide variety of…

Logic in Computer Science · Computer Science 2011-07-11 Johan Wittocx , Marc Denecker , Maurice Bruynooghe

We consider the problem of the computation of $\inf_p \theta p$ over the set of exponent pairs $P \ni p$ under linear constraints for a certain class of objective functions $\theta$. An effective algorithm is presented. The output of the…

Number Theory · Mathematics 2014-12-24 Andrew V. Lelechenko

To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs contain both decision variables, which we can set, and stochastic…

Artificial Intelligence · Computer Science 2009-03-09 S. Armagan Tarim , Suresh Manandhar , Toby Walsh

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

Concurrent Constraint Programming (CCP) is a simple and powerful model for concurrency where agents interact by telling and asking constraints. Since their inception, CCP-languages have been designed for having a strong connection to logic.…

Logic in Computer Science · Computer Science 2020-02-19 Elaine Pimentel , Carlos Olarte , Vivek Nigam

We take up an idea from the folklore of Answer Set Programming, namely that choices, integrity constraints along with a restricted rule format is sufficient for Answer Set Programming. We elaborate upon the foundations of this idea in the…

Artificial Intelligence · Computer Science 2021-11-25 Jorge Fandinno , Seemran Mishra , Javier Romero , Torsten Schaub

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

Incorporating constraints is a major concern in probabilistic machine learning. A wide variety of problems require predictions to be integrated with reasoning about constraints, from modelling routes on maps to approving loan predictions.…

Machine Learning · Computer Science 2020-01-31 Ioannis Papantonis , Vaishak Belle

String analysis is the problem of reasoning about how strings are manipulated by a program. It has numerous applications including automatic detection of cross-site scripting (XSS). A popular string analysis technique includes symbolic…

Logic in Computer Science · Computer Science 2020-11-02 Lukas Holik , Petr Janku , Anthony W. Lin , Philipp Rümmer , Tomas Vojnar

This paper studies how to verify the conformity of a program with its specification and proposes a novel constraint-programming framework for bounded program verification (CPBPV). The CPBPV framework uses constraint stores to represent the…

Software Engineering · Computer Science 2008-07-16 Hélène Collavizza , Michel Rueher , Pascal Van Hentenryck

In various applications the search for certificates for certain properties (e.g., stability of dynamical systems, program termination) can be formulated as a quantified constraint solving problem with quantifier prefix exists-forall. In…

Logic in Computer Science · Computer Science 2014-06-26 Milan Hladík , Stefan Ratschan

We document a connection between constraint reasoning and probabilistic reasoning. We present an algorithm, called {em probabilistic arc consistency}, which is both a generalization of a well known algorithm for arc consistency used in…

Artificial Intelligence · Computer Science 2013-01-18 Michael C. Horsch , Bill Havens

We show that several constraint propagation algorithms (also called (local) consistency, consistency enforcing, Waltz, filtering or narrowing algorithms) are instances of algorithms that deal with chaotic iteration. To this end we propose a…

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

The recent series 5 of the ASP system clingo provides generic means to enhance basic Answer Set Programming (ASP) with theory reasoning capabilities. We instantiate this framework with different forms of linear constraints, discuss the…

Artificial Intelligence · Computer Science 2017-07-14 Tomi Janhunen , Roland Kaminski , Max Ostrowski , Torsten Schaub , Sebastian Schellhorn , Philipp Wanko

Constraints that may be obtained by composition from simpler constraints are present, in some way or another, in almost every constraint program. The decomposition of such constraints is a standard technique for obtaining an adequate…

Artificial Intelligence · Computer Science 2013-01-21 Marco Correia , Pedro Barahona

We introduce an inductive logic programming approach that combines classical divide-and-conquer search with modern constraint-driven search. Our anytime approach can learn optimal, recursive, and large programs and supports predicate…

Artificial Intelligence · Computer Science 2021-12-08 Andrew Cropper
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