Towards an Immune System that solves CSP

LES AUTEURS : María-Cristina Riff and Marcos Zúñiga

RESUME:

Constraint satisfaction problems (CSPs) widely occur in artificial intelligence. In the last twenty years, many algorithms and heuristics were developed to solve CSP. Recently, bio-inspired algorithms have been proposed to solve CSP. They have shown to be more efficient than systematic approaches in
solving hard instances. Given that recent publications indicate that Immune systems offer advantages to solve complex problems, our aim here is to propose an efficient immune system which can solve CSPs. We propose an immune system which is able to solve hard constraint satisfaction problems. The tests were carried out using random generated binary constraint satisfaction problems on the transition phase.

Mots clé: artificial immune systems, constraint satisfaction problems.

Pour télécharger cet article,  cliquez ici

BibTeX reference:

@InProceedings{riffzuniga2007,
author = {M.-C. Riff and M. Z\'u$\tilde{\mathrm n}$iga},
title = {Towards an Immune System that solves CSP},
booktitle = {Proceedings of the IEEE Congress on Evolutionary 
Computation (CEC2007)},
address = {Singapore},
year = {2007},
month = {25-28 September},
note =         {To appear.}
}