Abstract
This work describes a method to control a behaviour of intelligent data mining agent We developed an adaptive decision making system that utilizes genetic programming technique to evolve an agent’s decision strategy. The parameters of data mining task and current state of an agent are taken into account by tree structures evolved by genetic programming. Efficiency of decision strategies is compared from the perspectives of single and multi criteria optimization.
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Šlapák, M., Neruda, R. (2014). Multiobjective Genetic Programming of Agent Decision Strategies. In: Kömer, P., Abraham, A., Snášel, V. (eds) Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014. Advances in Intelligent Systems and Computing, vol 303. Springer, Cham. https://doi.org/10.1007/978-3-319-08156-4_18
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DOI: https://doi.org/10.1007/978-3-319-08156-4_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08155-7
Online ISBN: 978-3-319-08156-4
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