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The linear programming (LP) approach is, together with value iteration and policy iteration, one of the three fundamental methods to solve optimal control problems in a dynamic programming setting. Despite its simple formulation,…

Systems and Control · Electrical Eng. & Systems 2023-10-31 Lucia Falconi , Andrea Martinelli , John Lygeros

Linear programming describes the problem of optimising a linear objective function over a set of constraints on its variables. In this paper we present a solver for linear programs implemented in the proof assistant Isabelle/HOL. This…

Logic in Computer Science · Computer Science 2024-03-29 Julian Parsert

A recent trend in object oriented (OO) programming languages is the use of Access Permissions (APs) as an abstraction for controlling concurrent executions of programs. The use of AP source code annotations defines a protocol specifying how…

Logic in Computer Science · Computer Science 2018-02-14 Carlos Olarte , Elaine Pimentel , Camilo Rueda

We describe a type system with mixed linear and non-linear recursive types called LNL-FPC (the linear/non-linear fixpoint calculus). The type system supports linear typing, which enhances the safety properties of programs, but also supports…

Programming Languages · Computer Science 2023-06-22 Bert Lindenhovius , Michael Mislove , Vladimir Zamdzhiev

Linear logic Concurrent Constraint programming (LCC) is an extension of concurrent constraint programming (CC) where the constraint system is based on Girard's linear logic instead of the classical logic. In this paper we address the…

Programming Languages · Computer Science 2011-08-02 Rémy Haemmerlé

Logic programming languages present clear advantages in terms of declarativeness and conciseness. However, the ideas of logic programming have been met with resistance in other programming communities, and have not generally been adopted by…

Programming Languages · Computer Science 2026-01-08 Ivan Perez , Angel Herranz

Structured output prediction problems (e.g., sequential tagging, hierarchical multi-class classification) often involve constraints over the output label space. These constraints interact with the learned models to filter infeasible…

Machine Learning · Computer Science 2021-06-14 Tao Meng , Kai-Wei Chang

Detectability of failures of linear programming (LP) decoding and its potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the LP problem. In this paper, we make a…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi N. , Paul H. Siegel

We present a new method for the constraint-based synthesis of termination arguments for linear loop programs based on linear ranking templates. Linear ranking templates are parameterized, well-founded relations such that an assignment to…

Logic in Computer Science · Computer Science 2019-03-14 Jan Leike , Matthias Heizmann

Logically constrained term rewriting is a relatively new rewriting formalism that naturally supports built-in data structures, such as integers and bit vectors. In the analysis of logically constrained term rewrite systems (LCTRSs),…

Logic in Computer Science · Computer Science 2025-12-16 Kanta Takahata , Jonas Schöpf , Naoki Nishida , Takahito Aoto

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

We present a new method for the constraint-based synthesis of termination arguments for linear loop programs based on linear ranking templates. Linear ranking templates are parametrized, well-founded relations such that an assignment to the…

Logic in Computer Science · Computer Science 2014-01-22 Jan Leike , Matthias Heizmann

In recent years they have been numerous works that aim to automate relational verification. Meanwhile, although Constrained Horn Clauses (CHCs) empower a wide range of verification techniques and tools, they lack the ability to express…

Programming Languages · Computer Science 2021-06-07 Hiroshi Unno , Tachio Terauchi , Eric Koskinen

We present a novel approach to modelling and learning vector fields from physical systems using neural networks that explicitly satisfy known linear operator constraints. To achieve this, the target function is modelled as a linear…

Machine Learning · Statistics 2021-04-29 Johannes Hendriks , Carl Jidling , Adrian Wills , Thomas Schön

String diagrams are a graphical language used to represent processes that can be composed sequentially or in parallel, which correspond graphically to horizontal or vertical juxtaposition. In this paper we demonstrate how to compute the…

Category Theory · Mathematics 2024-04-04 Celia Rubio-Madrigal , Jules Hedges

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

CLASS is a proof-of-concept general purpose linear programming language, flexibly supporting realistic concurrent programming idioms, and featuring an expressive linear type system ensuring that programs (1) never misuse or leak stateful…

Programming Languages · Computer Science 2025-05-28 Luís Caires

A class of valued constraint satisfaction problems (VCSPs) is characterised by a valued constraint language, a fixed set of cost functions on a finite domain. An instance of the problem is specified by a sum of cost functions from the…

Computational Complexity · Computer Science 2015-11-24 Johan Thapper , Stanislav Zivny

A novel formalisation of variable control in languages with implicit names based on de Bruijn indices is presented. We design and implement three languages: first, a restricted language with implicit names; then, a restricted calculus with…

Logic in Computer Science · Computer Science 2026-01-14 Silvia Ghilezan , Jelena Ivetić , Pierre Lescanne , Simona Kašterović

A new computationally simple method of imposing hard convex constraints on the neural network output values is proposed. The key idea behind the method is to map a vector of hidden parameters of the network to a point that is guaranteed to…

Machine Learning · Computer Science 2023-07-21 Andrei V. Konstantinov , Lev V. Utkin