Plastic Fitness Predictors Coevolved with Cartesian Programs

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU121578" target="_blank" >RIV/00216305:26230/16:PU121578 - isvavai.cz</a>
Result on the web
<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=11001" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=11001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-30668-1_11" target="_blank" >10.1007/978-3-319-30668-1_11</a>

Result language
angličtina
Original language name
Plastic Fitness Predictors Coevolved with Cartesian Programs
Original language description
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.
Czech name
—
Czech description
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Project
<a href="/en/project/GA14-04197S" target="_blank" >GA14-04197S: Advanced Methods for Evolutionary Design of Complex Digital Circuits</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

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

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