Feature Extraction for Surrogate Models in Genetic Programming

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F16%3A00466883" target="_blank" >RIV/67985807:_____/16:00466883 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/16:10333210
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-45823-6_31" target="_blank" >http://dx.doi.org/10.1007/978-3-319-45823-6_31</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-45823-6_31" target="_blank" >10.1007/978-3-319-45823-6_31</a>

Result language
angličtina
Original language name
Feature Extraction for Surrogate Models in Genetic Programming
Original language description
We discuss the use of surrogate models in the field of genetic programming. We describe a set of features extracted from each tree and use it to train a model of the fitness function. The results indicate that such a model can be used to predict the fitness of new individuals without the need to evaluate them. In a series of experiments, we show how surrogate modeling is able to reduce the number of fitness evaluations needed in genetic programming, and we discuss how the use of surrogate models affects the exploration and convergence of genetic programming algorithms.
Czech name
—
Czech description
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Project
<a href="/en/project/GA15-19877S" target="_blank" >GA15-19877S: Automated Knowledge and Plan Modeling for Autonomous Robots</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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