An Improved Single Node Genetic Programming for Symbolic Regression
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F15%3A00239851" target="_blank" >RIV/68407700:21730/15:00239851 - isvavai.cz</a>
Result on the web
<a href="http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=MIWqy6ryvpE=&t=1" target="_blank" >http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=MIWqy6ryvpE=&t=1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0005598902440251" target="_blank" >10.5220/0005598902440251</a>
Alternative languages
Result language
angličtina
Original language name
An Improved Single Node Genetic Programming for Symbolic Regression
Original language description
We have proposed three extensions of the standard Single Node GP, namely (1) a selection strategy for choosing nodes to be mutated based on the depth of the nodes, (2) operators for placing a compact version of the best tree to the beginning and to the end of the population, and (3) a local search strategy with multiple mutations applied in each iteration. All the proposed modifications have been experimentally evaluated on five symbolic regression problems and compared with standard GP and SNGP. The achieved results are promising showing the potential of the proposed modifications to significantly improve the performance of the SNGP algorithm
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA15-22731S" target="_blank" >GA15-22731S: Symbolic Regression for Reinforcement Learning in Continuous Spaces</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 7th International Joint Conference on Computational Intelligence
ISBN
978-989-758-157-1
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
244-251
Publisher name
INSTICC Press
Place of publication
Setúbal
Event location
Lisabon
Event date
Nov 12, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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