Ing. Michaela Drahoąová

WIGLASZ Michal and DRAHO©OVÁ Michaela. Plastic Fitness Predictors Coevolved with Cartesian Programs. In: 19th European Conference on Genetic programming. Berlin: Springer International Publishing, 2016, pp. 164-179. ISBN 978-3-319-30667-4.
Publication language:english
Original title:Plastic Fitness Predictors Coevolved with Cartesian Programs
Title (cs):Koevoluce plastických prediktorů fitness a kartézských programů
Pages:164-179
Proceedings:19th European Conference on Genetic programming
Conference:19th European Conference on Genetic Programming
Series:LNCS 9594
Place:Berlin, DE
Year:2016
ISBN:978-3-319-30667-4
DOI:10.1007/978-3-319-30668-1_11
Publisher:Springer International Publishing
Keywords
fitness predictors, cartesian genetic programming, coevolution, phenotypic plasticity
Annotation
Coevolution of fitness predictors, which are a small sample of all training data for a particular task, was successfully used to reduce the computational cost of the design performed by cartesian genetic programming. However, it is necessary to specify the most advantageous number of fitness cases in predictors, which differs from task to task. This paper proposes to introduce a new type of directly encoded fitness predictors inspired by the principles of phenotypic plasticity. The size of the coevolved fitness predictor is adapted in response to the phase of learning that the program evolution goes through. It is shown in 5 symbolic regression tasks that the proposed algorithm is able to adapt the number of fitness cases in predictors in response to the solved task and the program evolution flow.
BibTeX:
@INPROCEEDINGS{
   author = {Michal Wiglasz and Michaela Draho{\v{s}}ov{\'{a}}},
   title = {Plastic Fitness Predictors Coevolved with Cartesian Programs},
   pages = {164--179},
   booktitle = {19th European Conference on Genetic programming},
   series = {LNCS 9594},
   year = {2016},
   location = {Berlin, DE},
   publisher = {Springer International Publishing},
   ISBN = {978-3-319-30667-4},
   doi = {10.1007/978-3-319-30668-1_11},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=11001}
}

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