Abstract
This paper presents an evolutionary algorithm applicable to the task of device adjustment in smart appliances ensembles. The algorithm requires very little environmental knowledge and is therefore complementary to the commonly applied rule based methods, such as ontologies. In contrast to traditional evolutionary algorithms, the new approach avoids any central processing scheme. Instead, the ensemble settings are distributed physically across all devices such that every parameter resides only in the device to which it belongs. This approach enables the correct handling of the dynamic nature of smart appliances ensembles, as will be shown in the course of the paper.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aarts, E.: Ambient intelligence: A multimedia perspective. IEEE Multimedia 11(1), 12–19 (2004)
Bäck, T., Hammel, U., Schwefel, H.-P.: Evolutionary Computation: Comments on the History and Current State. IEEE Transactions on Evolutionary Computation 1(1), 3–17 (1997)
Bry, F., Hattori, T., Hiramatsu, K., Okadome, T., Wieser, C., Yamada, T.: Context Modeling in OWL for Smart Building Services. In: Brass, S., Goldberg, C. (eds.) Tagungsband zum 17. GI-Workshop über Grundlagen von Datenbanken, Wörlitz, Germany, Gesellschaft für Informatik, Institute of Computer Science, Martin-Luther-Univerity Halle-Wittenberg, pp. 38–42 (2005)
Chen, H., Perich, F., Finin, T., Joshi, A.: SOUPA: Standard Ontology for Ubiquitous and Pervasive Applications. In: International Conference on Mobile and Ubiquitous Systems: Networking and Services, Boston, MA (2004)
Fogel, D.B.: Evolutionary Computation: Toward a New Philosophy of Machine Learning Intelligence. IEEE Press, NJ (1995)
Lee, C.-Y., Antonsson, E.K.: Variable Length Genomes for Evolutionary Algorithms. In: Whitley, L.D., Goldberg, D.E., Cantú-Paz, E., Spector, L., Parmee, I.C., Beyer, H.-G. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2000), p. 806 (2000)
Rechenberg, I.: Evolutionsstrategie, Frommann-Holzboog, Stuttgart (1994)
Saha., D., Mukherjee, A.: Pervasive computing: A paradigm for the 21st century. IEEE Computer, 25–31
Schiffmann, W., Joost, M., Werner, R.: Application of Genetic Algorithms to the Construction of Topologies for Multilayer Perceptrons. In: Proceedings of Artificial Neural Networks and Genetic Algorithms, pp. 675–682 (1993)
Weiser, M.: Some computer science issues in ubiquitous computing. Communications of the ACM 26(7), 75–84 (1993)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Goldmann, S., Salomon, R. (2008). ESO: Evolutionary Self-organization in Smart-Appliances Ensembles. In: Dengel, A.R., Berns, K., Breuel, T.M., Bomarius, F., Roth-Berghofer, T.R. (eds) KI 2008: Advances in Artificial Intelligence. KI 2008. Lecture Notes in Computer Science(), vol 5243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85845-4_26
Download citation
DOI: https://doi.org/10.1007/978-3-540-85845-4_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85844-7
Online ISBN: 978-3-540-85845-4
eBook Packages: Computer ScienceComputer Science (R0)