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Abstract Domains In Constraint Programming 1st Edition Marie Pelleau

  • SKU: BELL-38250134
Abstract Domains In Constraint Programming 1st Edition Marie Pelleau
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Abstract Domains In Constraint Programming 1st Edition Marie Pelleau instant download after payment.

Publisher: ISTE Press - Elsevier
File Extension: PDF
File size: 1.13 MB
Pages: 176
Author: Marie Pelleau
ISBN: 9781785480102, 1785480103
Language: English
Year: 2015
Edition: 1

Product desciption

Abstract Domains In Constraint Programming 1st Edition Marie Pelleau by Marie Pelleau 9781785480102, 1785480103 instant download after payment.

Constraint Programming aims at solving hard combinatorial problems, with a computation time increasing in practice exponentially. The methods are today efficient enough to solve large industrial problems, in a generic framework. However, solvers are dedicated to a single variable type: integer or real. Solving mixed problems relies on ad hoc transformations. In another field, Abstract Interpretation offers tools to prove program properties, by studying an abstraction of their concrete semantics, that is, the set of possible values of the variables during an execution. Various representations for these abstractions have been proposed. They are called abstract domains. Abstract domains can mix any type of variables, and even represent relations between the variables.
In this work, we define abstract domains for Constraint Programming, so as to build a generic solving method, dealing with both integer and real variables. We also study the octagons abstract domain, already defined in Abstract Interpretation. Guiding the search by the octagonal relations, we obtain good results on a continuous benchmark. We also define our solving method using Abstract Interpretation techniques, in order to include existing abstract domains. Our solver, AbSolute, is able to solve mixed problems and use relational domains.
- Exploits the over-approximation methods to integrate AI tools in the methods of CP
- Exploits the relationships captured to solve continuous problems more effectively
- Learn from the developers of a solver capable of handling practically all abstract domains

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