Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal on Interactive Systems |
Texto Completo: | https://sol.sbc.org.br/journals/index.php/jis/article/view/671 |
Resumo: | Real time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model coordination as a task allocation problem, in which specific tasks must be properly assigned to agents. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. A fitness estimation method is employed to accelerate execution of the genetic algorithm. To evaluate this approach, we implement this coordination mechanism in the AI of a popular video game: StarCraft: BroodWar. Experiment results show that the genetic algorithm successfully adjusts task allocation parameters. Besides, we assess the trade-off between solution quality and execution time of the genetic algorithm with fitness estimation. |
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Journal on Interactive Systems |
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Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy gameReal time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model coordination as a task allocation problem, in which specific tasks must be properly assigned to agents. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. A fitness estimation method is employed to accelerate execution of the genetic algorithm. To evaluate this approach, we implement this coordination mechanism in the AI of a popular video game: StarCraft: BroodWar. Experiment results show that the genetic algorithm successfully adjusts task allocation parameters. Besides, we assess the trade-off between solution quality and execution time of the genetic algorithm with fitness estimation.Nenhum resumo disponívelBrazilian Computer Society2017-09-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://sol.sbc.org.br/journals/index.php/jis/article/view/67110.5753/jis.2017.671Journal of Interactive Systems; v. 8 n. 1 (2017)Journal on Interactive Systems; Vol. 8 No. 1 (2017)2763-7719reponame:Journal on Interactive Systemsinstname:Sociedade Brasileira de Computação (SBC)instacron:SBCenghttps://sol.sbc.org.br/journals/index.php/jis/article/view/671/666Tavares, Anderson R.Zuin, Gianlucca LodronAzpúrua, HéctorChaimowicz, Luizinfo:eu-repo/semantics/openAccess2020-09-05T16:09:09Zoai:ojs2.sol.sbc.org.br:article/671Revistahttps://sol.sbc.org.br/journals/index.php/jis/ONGhttps://sol.sbc.org.br/journals/index.php/jis/oaijis@sbc.org.br2763-77192763-7719opendoar:2020-09-05T16:09:09Journal on Interactive Systems - Sociedade Brasileira de Computação (SBC)false |
dc.title.none.fl_str_mv |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game |
title |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game |
spellingShingle |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game Tavares, Anderson R. |
title_short |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game |
title_full |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game |
title_fullStr |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game |
title_full_unstemmed |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game |
title_sort |
Combining genetic algorithm and swarm intelligence for task allocation in a real time strategy game |
author |
Tavares, Anderson R. |
author_facet |
Tavares, Anderson R. Zuin, Gianlucca Lodron Azpúrua, Héctor Chaimowicz, Luiz |
author_role |
author |
author2 |
Zuin, Gianlucca Lodron Azpúrua, Héctor Chaimowicz, Luiz |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Tavares, Anderson R. Zuin, Gianlucca Lodron Azpúrua, Héctor Chaimowicz, Luiz |
description |
Real time strategy games are complex scenarios where multiple agents must be coordinated in a dynamic, partially observable environment. In this work, we model coordination as a task allocation problem, in which specific tasks must be properly assigned to agents. We employ a task allocation algorithm based on swarm intelligence and adjust its parameters using a genetic algorithm. A fitness estimation method is employed to accelerate execution of the genetic algorithm. To evaluate this approach, we implement this coordination mechanism in the AI of a popular video game: StarCraft: BroodWar. Experiment results show that the genetic algorithm successfully adjusts task allocation parameters. Besides, we assess the trade-off between solution quality and execution time of the genetic algorithm with fitness estimation. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-09-14 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://sol.sbc.org.br/journals/index.php/jis/article/view/671 10.5753/jis.2017.671 |
url |
https://sol.sbc.org.br/journals/index.php/jis/article/view/671 |
identifier_str_mv |
10.5753/jis.2017.671 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://sol.sbc.org.br/journals/index.php/jis/article/view/671/666 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Brazilian Computer Society |
publisher.none.fl_str_mv |
Brazilian Computer Society |
dc.source.none.fl_str_mv |
Journal of Interactive Systems; v. 8 n. 1 (2017) Journal on Interactive Systems; Vol. 8 No. 1 (2017) 2763-7719 reponame:Journal on Interactive Systems instname:Sociedade Brasileira de Computação (SBC) instacron:SBC |
instname_str |
Sociedade Brasileira de Computação (SBC) |
instacron_str |
SBC |
institution |
SBC |
reponame_str |
Journal on Interactive Systems |
collection |
Journal on Interactive Systems |
repository.name.fl_str_mv |
Journal on Interactive Systems - Sociedade Brasileira de Computação (SBC) |
repository.mail.fl_str_mv |
jis@sbc.org.br |
_version_ |
1796797410994814976 |