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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" }