Abstract
In the paper an immunological selection mechanism in the agent-based evolutionary computation is discussed. Since it allows to reduce the number of fitness assignments, it is especially useful for problems with high computational cost of individual’s evaluation. A neural network architecture optimization is considered as an example of such a problem. Selected experimental results obtained for the particular system dedicated to time-series prediction conclude the work.
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Byrski, A., Kisiel-Dorohinicki, M., Nawarecki, E. (2007). Immunological Selection in Agent-Based Optimization of Neural Network Parameters. In: Wegrzyn-Wolska, K.M., Szczepaniak, P.S. (eds) Advances in Intelligent Web Mastering. Advances in Soft Computing, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72575-6_10
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DOI: https://doi.org/10.1007/978-3-540-72575-6_10
Publisher Name: Springer, Berlin, Heidelberg
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