Abstracting soft constraints: framework, properties, examples

  • Authors:

  • Stefano Bistarelli;Philippe Codognet;Francesca Rossi

  • Affiliations:

  • C.N.R., Istituto per le Applicazioni Telematiche Area della Ricerca di Pisa, Via G. Moruzzi 1, Pisa, Italy;University of Paris 6, LIP6, case 169, 4, Place Jussieu, 75 252 Paris cedex 05, France;Università di Padova, Dipartimento di Matematica Pura ed Applicata, Via G. B. Belzoni 7, 35131 Padova, Italy

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2002

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Abstract

Soft constraints are very flexible and expressive. However, they are also very complex to handle. For this reason, it may be reasonable in several cases to pass to an abstract version of a given soft constraint problem, and then to bring some useful information from the abstract problem to the concrete one. This will hopefully make the search for a solution, or for an optimal solution, of the concrete problem, faster.In this paper we propose an abstraction scheme for soft constraint problems and we study its main properties. We show that processing the abstracted version of a soft constraint problem can help us in finding good approximations of the optimal solutions, or also in obtaining information that can make the subsequent search for the best solution easier.We also show how the abstraction scheme can be used to devise new hybrid algorithms for solving soft constraint problems, and also to import constraint propagation algorithms from the abstract scenario to the concrete one. This may be useful when we don't have any (or any efficient) propagation algorithm in the concrete setting.