Publication Details

Visualisation and Analysis of Genetic Records Produced by Cartesian Genetic Programming

SEKANINA, L.; KAPUSTA, V. Visualisation and Analysis of Genetic Records Produced by Cartesian Genetic Programming. In GECCO'16 Companion. New York: Association for Computing Machinery, 2016. p. 1411-1418. ISBN: 978-1-4503-4323-7.
Czech title
Vizualizace a analýza genetických záznamů produkovaných kartézským genetickým programováním
Type
conference paper
Language
English
Authors
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
Kapusta Vlastimil, Ing.
Keywords

Cartesian genetic programming, Digital circuit, Visualisation

Abstract

Cartesian genetic programming (CGP) is a branch of genetic programming in which candidate designs are represented using directed acyclic graphs. Evolutionary circuit design is the most typical application of CGP. This paper presents a new software tool - CGPAnalyzer - developed to analyse and visualise a genetic record (i.e. a log file) generated by CGP-based circuit design software. CGPAnalyzer automatically finds key genetic improvements in the genetic record and presents relevant phenotypes. The comparison module of CGPAnalyzer allows the user to select two phenotypes and compare their structure, history and functionality. It thus enables to reconstruct the process of discovering new circuit designs. This feature is demonstrated by means of the analysis of the genetic record from a 9-parity circuit evolution. The CGPAnalyzer tool is a desktop application with a graphical user interface created using Java v.8 and Swing library.  

Published
2016
Pages
1411–1418
Proceedings
GECCO'16 Companion
ISBN
978-1-4503-4323-7
Publisher
Association for Computing Machinery
Place
New York
DOI
10.1145/2908961.2931740
UT WoS
000383741800196
EID Scopus
2-s2.0-84986257311
BibTeX 
@inproceedings{BUT130962,
  author="Lukáš {Sekanina} and Vlastimil {Kapusta}",
  title="Visualisation and Analysis of Genetic Records Produced by Cartesian Genetic Programming",
  booktitle="GECCO'16 Companion",
  year="2016",
  pages="1411--1418",
  publisher="Association for Computing Machinery",
  address="New York",
  doi="10.1145/2908961.2931740",
  isbn="978-1-4503-4323-7",
  url="https://www.fit.vut.cz/research/publication/11141/"
}
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