Abstract
This paper deals with using an evolutionary algorithm (EA) as a prototyping tool to develop and refine a multi agents system (MAS) for problem solving. In the case of (distributed) solving, MAS may lack some knowledge about the solving mechanism. Using a GA as a prototyping tool thus enables to extract heuristics for use in the MAS design. This approach, based upon a model conciliating both EA and MAS perspectives, is tested on the antenna parameter setting problem (APSP) from the field of radiomobile networks. We demonstrate the feasibility and interest of such an approach for complex problems. Moreover, we advocate the use of MAS techniques for the field of radiomobile networks.
Preview
Unable to display preview. Download preview PDF.
Bibliography
Beasley D, Bull D.R., Martin R.R. (1993). An Overview of Genetic Algorithms. University Computing.
Briot J.P. (1988). From Objects to Actors: Study of a Limited Symbiosis in Smalltalk-80. Research Report RXF-LITP, nℴ88-58.
Cardozo E., Sichman J.S., Demazeau Y. (1993). Using the Active Object Model to Implement Multi-Agent Systems. In Proc. of the 5 th IEEE Int. Conf. on Tools with Artificial Intelligence.
Durfee E.H., Rosenschein J.S. (1994). Distributed Problem Solving and Multi-Agent Systems: Comparisons and Examples.
Ferber J. (1995). Les systèmes multi-agents: vers une intelligence collective. InterEditions.
Ferber J., Jacopin E. (1991). The framework of EcoProblem Solving. Decentralized AI, vol. 2. Elsevier.
Goldberg D.E. (1994). Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley.
Groupe de travail “Collectif” IAD/SMA de AFCET/AFIA (1997). Emergence et Systèmes Multi-agents. In Actes des 5ème Journées Francophones d'Intelligence Artificielle et Systèmes Multi-Agents, pp 323–341. Hermes.
Guedira K. (1993). MASC: une approche multi-agents des problèmes de satisfaction de contraintes. Thèse de Doctorat, Ecole Nationale Supérieure de l'Aeronautique et de l'Espace.
Guisnet B. (1996). La propagation pour les services de mobilité. Les Communications avec les Mobiles.
Hao J.K., Galinier P., Habib M., Méthodes heuristiques pour l'optimisation combinatoire et l'affectation sous contraintes. In Actes des 6èmes journées nationales, PRC-GDR IA, pp 107–144. Hermes.
Labidi S., Lejouad W. (1993). De l'Intelligence Artificielle Distribuée aux Systèmes Multi-Agents. Rapport de recherche nℴ2004. INRIA.
Magnin L. (1996). Modélisation et simulation de l'environnement dans les systèmes multi-agents — Application aux robots footballeurs. Thèse de doctorat. Université Paris VI.
Matthews D. GALIB a C++ Library of Genetic Algorithm Components, http://lancet.mit.edu/ga/.
Renaud D., A. Caminada (1997). Evolutionary Methods and Operators for Frequency Assignment Problem. SpeedUp Journal, vol. 11, nr. 2, pp. 27–32.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lissajoux, T., Hilaire, V., Koukam, A., Caminada, A. (1998). Genetic algorithms as prototyping tools for multi-agent systems: Application to the antenna parameter setting problem. In: Albayrak, S., Garijo, F.J. (eds) Intelligent Agents for Telecommunication Applications. IATA 1998. Lecture Notes in Computer Science, vol 1437. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0053941
Download citation
DOI: https://doi.org/10.1007/BFb0053941
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64720-1
Online ISBN: 978-3-540-69102-0
eBook Packages: Springer Book Archive