Conference paper

SEKANINA Lukáš and KAPUSTA Vlastimil. Visualisation and Analysis of Genetic Records Produced by Cartesian Genetic Programming. In: GECCO'16 Companion. New York: Association for Computing Machinery, 2016, pp. 1411-1418. ISBN 978-1-4503-4323-7.
Publication language:english
Original title:Visualisation and Analysis of Genetic Records Produced by Cartesian Genetic Programming
Title (cs):Vizualizace a analýza genetických záznamů produkovaných kartézským genetickým programováním
Proceedings:GECCO'16 Companion
Conference:Genetic and Evolutionary Computations Conference 2016
Place:New York, US
Publisher:Association for Computing Machinery
+Type Name Title Size Last modified
iconvizgecco16.pdf1,1 MB2016-07-28 11:04:27
^ Select all
With selected:
Cartesian genetic programming, Digital circuit, Visualisation
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.  
   author = {Luk{\'{a}}{\v{s}} Sekanina and Vlastimil Kapusta},
   title = {Visualisation and Analysis of Genetic Records
	Produced by Cartesian Genetic Programming},
   pages = {1411--1418},
   booktitle = {GECCO'16 Companion},
   year = 2016,
   location = {New York, US},
   publisher = {Association for Computing Machinery},
   ISBN = {978-1-4503-4323-7},
   doi = {10.1145/2908961.2931740},
   language = {english},
   url = {}

Your IPv4 address:
Switch to https