From Darwinian Evolution to Swarm Computation and Gamesourcing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F19%3A10244899" target="_blank" >RIV/61989100:27740/19:10244899 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27240/19:10244899

Výsledek na webu

<a href="https://www.taylorfrancis.com/books/e/9781315167084/chapters/10.1201/9781315167084-7" target="_blank" >https://www.taylorfrancis.com/books/e/9781315167084/chapters/10.1201/9781315167084-7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1201/9781315167084" target="_blank" >10.1201/9781315167084</a>

Jazyk výsledku

angličtina

Název v původním jazyce

From Darwinian Evolution to Swarm Computation and Gamesourcing

Popis výsledku v původním jazyce

This chapter discusses how to generate a network reflecting the behavior of selected evolutionary and swarm algorithms as much as possible to make a thorough analysis of relationships between individuals in the population. Such analysis is considered to be the starting point in the process of development of enhanced algorithms, where the results of the analysis are incorporated. The chapter investigates if there is a connection between an individual with the best fitness value and a node with the highest out-degree. Clustering coefficients of short-interval networks (SIN) generated on the basis of the differential evolution (DE) algorithms are very small; however, there are statistically significant differences between clustering coefficients of networks generated on the basis of the different DE algorithms. The principle of SINs creation as well as the principle of DE algorithms has caused very low density of networks.

Název v anglickém jazyce

From Darwinian Evolution to Swarm Computation and Gamesourcing

Popis výsledku anglicky

This chapter discusses how to generate a network reflecting the behavior of selected evolutionary and swarm algorithms as much as possible to make a thorough analysis of relationships between individuals in the population. Such analysis is considered to be the starting point in the process of development of enhanced algorithms, where the results of the analysis are incorporated. The chapter investigates if there is a connection between an individual with the best fitness value and a node with the highest out-degree. Clustering coefficients of short-interval networks (SIN) generated on the basis of the differential evolution (DE) algorithms are very small; however, there are statistically significant differences between clustering coefficients of networks generated on the basis of the different DE algorithms. The principle of SINs creation as well as the principle of DE algorithms has caused very low density of networks.

Druh

C - Kapitola v odborné knize

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

From Parallel to Emergent Computing

ISBN

978-1-351-68191-9

Počet stran výsledku

42

Strana od-do

135-176

Počet stran knihy

608

Název nakladatele

CRC Press

Místo vydání

Boca Raton

Kód UT WoS kapitoly

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