Graph-based Genetic Programming

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU146650" target="_blank" >RIV/00216305:26230/22:PU146650 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1145/3520304.3533657" target="_blank" >http://dx.doi.org/10.1145/3520304.3533657</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3520304.3533657" target="_blank" >10.1145/3520304.3533657</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Graph-based Genetic Programming

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Graph-based Genetic Programming

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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

ISBN

978-1-4503-9268-6

ISSN

—

e-ISSN

—

Počet stran výsledku

25

Strana od-do

958-982

Název nakladatele

Association for Computing Machinery

Místo vydání

Boston

Místo konání akce

Boston

Datum konání akce

9. 7. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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