Abstract
In this paper we present the research results about the adequation of evolutionary algorithms and multi-agent systems to learn user's preferences during his interactions with a digital assistant. This study is done in the framework of “broadcasting” on the Internet. In our experiment, a multi-agent system with a Genetic Algorithm is used to globally optimize a user's selection of “channels” among a very large number of choices. We show that this approach could solve the problem of providing multiple optimal solutions without losing diversity.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Ackley D., Littman M. (1991). Interactions Between Learning and Evolution.
Artificial Life II. SFI Studies in the Siences of Complexity, vol. X, eddited by C.G. Langton, C. Taylor, J.D. Farmer, S. Rasmussen, Addison-Wesley.
Booker L.B. (1982). Intelligent Behavior as an Adaptation to the Task Environment. Doctoral Dissertation, Technical Report n. 243, University of Michigan, Ann Arbor.
Eshelman L., Schaffer J.D. (1993). Real-coded Genetic Algorithms and Interval-Schemata. In Foundations of Genetic Algorithms 2, p. 187–202, edited by L.D. Whitley, Morgan Kaufmann, Los Altos.
Ferber J. (1995). Les Systèmes Multi-Agents, p. 15, InterEditions.
Gilles A., Lebiannic Y., Montet P., Heudin J.C. (1991). A Parallel Multi-Expert Architecture for the Copilote Electronique. 11th International Conference on Expert Systems and their applications, EC2, Avignon, France.
Goldberg D.A. (1989). Genetic Algorithms in Search, Optimization & Machine Learning. p 121–124, Addison-Wesley.
Gosling J. (1994). The Java Language: A White paper. Sun Microsystems.
Heudin J.C. (1994). La Vie Artificielle. Hermès, Paris.
Langton C.G. (1988). Artificial Life. Artificial Life. SFI Studies in the Sciences of Complexity, vol. VI, edited by C.G. Langton. Addison-Wesley.
Lemay L. (1997). The Official Marimba Guide to Castanet. Sams.Net.
Rechenberg I. (1973). Evolutionstrategie: Optimierung Technisher Systeme nach Prinzipien des Biologischen Evolution. Fromman-Holzboog Verlag, Stuttgart.
Rosenschein J.S., Zlotkin G. (1994). Designing Conventions for Automated Negotiation, AI Magazine, Vol. 15, n. 3, p. 29, AAAI, Menlo Park.
Sheth B., Maes P. (1993). Evolving Agents for Personalized Information Filtering, Proceedings of the Ninth Conference on Artificial Intelligence for Applications '93, Orlando, Florida, IEEE Computer Society Press
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cuenca, C., Heudin, JC. (1998). An agent system for learning profiles in broadcasting applications on the Internet. In: Hao, JK., Lutton, E., Ronald, E., Schoenauer, M., Snyers, D. (eds) Artificial Evolution. AE 1997. Lecture Notes in Computer Science, vol 1363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0026594
Download citation
DOI: https://doi.org/10.1007/BFb0026594
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64169-8
Online ISBN: 978-3-540-69698-8
eBook Packages: Springer Book Archive