Abstract
Smart-appliances ensembles are highly dynamic device collections in which devices can leave and join at any time without notice. Due to the high system dynamics, such ensembles cannot employ standard evolutionary algorithms for their internal self-organization processes. Therefore, this paper proposes a new evolutionary framework, called the appliances-go-evolution platform (AGE-P). The simulation experiments indicate that AGE-P is able to properly cope with the peculiarities of smart-appliances ensembles and that it is thus a suitable option for their self-organization processes.
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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, pp. 38–42. Institute of Computer Science, Martin-Luther-Univerity Halle-Wittenberg (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)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
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)
Ramsey, C.L., De Jong, K.A., Grefenstette, J.J., Wu, A.S., Burke, D.S.: Genome Length as an Evolutionary Self-Adaptation. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) Proceedings of Fifth International Conference on Parallel Problem Solving from Nature (PPSN V), pp. 27–30 (1998)
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)
Schwefel, H.-P.: Evolution and Optimum Seeking. John Wiley and Sons, NY (1995)
Weiser, M.: Some computer science issues in ubiquitous computing. Communications of the ACM 26(7), 75–84 (1993)
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Salomon, R., Goldmann, S. (2008). AGE-P: A Platform for Open Evolution. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_110
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DOI: https://doi.org/10.1007/978-3-540-87700-4_110
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