Detail publikace

Graph-based Genetic Programming

KALKREUTH, R. DAL PICCOL SOTTO, L. VAŠÍČEK, Z.

Originální název

Graph-based Genetic Programming

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Although the classical way to represent programs in Genetic Programming (GP) is by means of an expression tree, different GP variants with alternative representations have been proposed throughout the years. One such representation is the Directed Acyclic Graph (DAG), adopted by methods like Cartesian Genetic Programming (CGP), Linear Genetic Programming (LGP), Parallel Distributed Genetic Programming (PDGP), and, more recently, Evolving Graphs by Graph Programming (EGGP). The aim of this tutorial is to consider this methods from a unified perspective as graph-based GP, present their historical background, representation features, operators, applications, and available implementations.

Klíčová slova

Genetic Programming, Cartesian Genetic Programming, Linear Genetic Programming, Parallel Distributed Genetic Programming

Autoři

KALKREUTH, R.; DAL PICCOL SOTTO, L.; VAŠÍČEK, Z.

Vydáno

8. 7. 2022

Nakladatel

Association for Computing Machinery

Místo

Boston

ISBN

978-1-4503-9268-6

Kniha

GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference

Strany od

958

Strany do

982

Strany počet

25

BibTex

@inproceedings{BUT180545,
  author="Roman {Kalkreuth} and Léo Françoso {Dal Piccol Sotto} and Zdeněk {Vašíček}",
  title="Graph-based Genetic Programming",
  booktitle="GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference",
  year="2022",
  pages="958--982",
  publisher="Association for Computing Machinery",
  address="Boston",
  doi="10.1145/3520304.3533657",
  isbn="978-1-4503-9268-6"
}