About: Santa Fe Trail for Artificial Ant with Analytic Programming and Three Evolutionary Algorithms     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Článek se zabývá novou metodou pro symbolickou regresi - Analytickým programováním (AP), který dokáže řešit různé problémy z oblasti symbolické regrese. Jedním z úkolů může být nastavení optimální trajektorie pro umělého mravence na stezce Santa FE. Kromě principů AP je zde osvětlené, jak AP bylo použito na nastavení trajektorie pro umělého mravence. Byly zde použity 3 evoluční algoritmy jako optimalizační nástroje - SOMA, DE a simulované žíhání (SA). Výsledky ukázaly, že je nutné zvolit vhodný optimalizační nástroj, protože simulované žíhání neobstálo tak dobře jako SOMA a DE. (cs)
  • The paper deals with a novelty tool for symbolic regression - Analytic Programming (AP) which is able to solve various problems from the symbolic regression domain. One of the tasks for it can be a setting an optimal trajectory for an artificial ant on Santa Fe trail which is the main application of Analytic Programming in this paper. In this contribution main principles of AP are described and explained. In the second part of the article how AP was used for a setting an optimal trajectory for the artificial ant according the user requirements is in detail described. An ability to create so called programs, as well as Genetic Programming (GP) or Grammatical Evolution (GE) do, is shown in that part. AP is a superstructure of evolutionary algorithms which are necessary to run AP. In this contribution 3 evolutionary algorithms were used - Self Organizing Migrating Algorithm, Differential Evolution and Simulated Annealing. The results show that the first two used algorithms were more successful than not s
  • The paper deals with a novelty tool for symbolic regression - Analytic Programming (AP) which is able to solve various problems from the symbolic regression domain. One of the tasks for it can be a setting an optimal trajectory for an artificial ant on Santa Fe trail which is the main application of Analytic Programming in this paper. In this contribution main principles of AP are described and explained. In the second part of the article how AP was used for a setting an optimal trajectory for the artificial ant according the user requirements is in detail described. An ability to create so called programs, as well as Genetic Programming (GP) or Grammatical Evolution (GE) do, is shown in that part. AP is a superstructure of evolutionary algorithms which are necessary to run AP. In this contribution 3 evolutionary algorithms were used - Self Organizing Migrating Algorithm, Differential Evolution and Simulated Annealing. The results show that the first two used algorithms were more successful than not s (en)
Title
  • Santa Fe Trail for Artificial Ant with Analytic Programming and Three Evolutionary Algorithms
  • Stezka Santa Fe pro umělého mravence s analytickým programováním a třemi evolučními algoritmy (cs)
  • Santa Fe Trail for Artificial Ant with Analytic Programming and Three Evolutionary Algorithms (en)
skos:prefLabel
  • Santa Fe Trail for Artificial Ant with Analytic Programming and Three Evolutionary Algorithms
  • Stezka Santa Fe pro umělého mravence s analytickým programováním a třemi evolučními algoritmy (cs)
  • Santa Fe Trail for Artificial Ant with Analytic Programming and Three Evolutionary Algorithms (en)
skos:notation
  • RIV/70883521:28140/07:63505862!RIV08-MSM-28140___
http://linked.open.../vavai/riv/strany
  • 334-339
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/05/0271), P(GA102/06/1132), Z(MSM7088352101)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 448875
http://linked.open...ai/riv/idVysledku
  • RIV/70883521:28140/07:63505862
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Evolutionary algorithms; symbolic regression; Santa Fe (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6F3651407B46]
http://linked.open...i/riv/mistoVydani
  • Phuket
http://linked.open...i/riv/nazevZdroje
  • AMS 2007
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Oplatková, Zuzana
  • Zelinka, Ivan
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society
https://schema.org/isbn
  • 0-7695-2845-7
http://localhost/t...ganizacniJednotka
  • 28140
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software