Symbolic Regression by Grammar-based Multi-Gene Genetic Programming
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00231783" target="_blank" >RIV/68407700:21230/15:00231783 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/15:00231783
Result on the web
<a href="http://dl.acm.org/citation.cfm?id=2768484&CFID=715756301&CFTOKEN=65340477" target="_blank" >http://dl.acm.org/citation.cfm?id=2768484&CFID=715756301&CFTOKEN=65340477</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2739482.2768484" target="_blank" >10.1145/2739482.2768484</a>
Alternative languages
Result language
angličtina
Original language name
Symbolic Regression by Grammar-based Multi-Gene Genetic Programming
Original language description
Grammatical Evolution is an algorithm of Genetic Programming but it is capable of evolving programs in an arbitrary language given by a user-provided context-free grammar. We present a way how to apply Multi-Gene idea, known from Multi-Gene Genetic Programming, to Grammatical Evolution, just by modifying the given grammar. We also describe modifications which improve the behavior of such algorithm, called Multi-Gene Grammatical Evolution. We compare the resulting system to GPTIPS, an existing implementation of MGGP.
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
S - Specificky vyzkum na vysokych skolach
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 Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference (GECCO 2015)
ISBN
978-1-4503-3488-4
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
1217-1220
Publisher name
ACM
Place of publication
New York
Event location
Madrid
Event date
Jul 11, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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