Detail publikačního výsledku

When Does Cartesian Genetic Programming Minimize the Phenotype Size Implicitly?

GAJDA, Z.; SEKANINA, L.

Originální název

When Does Cartesian Genetic Programming Minimize the Phenotype Size Implicitly?

Anglický název

When Does Cartesian Genetic Programming Minimize the Phenotype Size Implicitly?

Druh

Stať ve sborníku mimo WoS a Scopus

Originální abstrakt

A new method is proposed to minimize the number of gates in combinational circuits using Cartesian Genetic Programming (CGP). We show that when the selection of the parent individual is performed on basis of its functionality solely (neglecting thus the phenotype size) smaller circuits can be evolved even if the number of gates is not considered by a fitness function. This phenomenon is confirmed on the evolutionary design of combinational multipliers.

Anglický abstrakt

A new method is proposed to minimize the number of gates in combinational circuits using Cartesian Genetic Programming (CGP). We show that when the selection of the parent individual is performed on basis of its functionality solely (neglecting thus the phenotype size) smaller circuits can be evolved even if the number of gates is not considered by a fitness function. This phenomenon is confirmed on the evolutionary design of combinational multipliers.

Klíčová slova

genetic programming, digital circuits, evolutionary design

Klíčová slova v angličtině

genetic programming, digital circuits, evolutionary design

Autoři

GAJDA, Z.; SEKANINA, L.

Rok RIV

2012

Vydáno

08.07.2010

Nakladatel

Association for Computing Machinery

Místo

New York

ISBN

978-1-4503-0072-8

Kniha

Proceeding of Genetic and Evolutionary Computation Conference, GECCO 2010

Strany od

983

Strany do

984

Strany počet

2

BibTex

@inproceedings{BUT35530,
  author="Zbyšek {Gajda} and Lukáš {Sekanina}",
  title="When Does Cartesian Genetic Programming Minimize the Phenotype Size Implicitly?",
  booktitle="Proceeding of Genetic and Evolutionary Computation Conference, GECCO 2010",
  year="2010",
  pages="983--984",
  publisher="Association for Computing Machinery",
  address="New York",
  isbn="978-1-4503-0072-8"
}