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Evolving behaviour trees for the Mario AI competition using grammatical evolution
Date Issued
2011-04-27
Date Available
2012-03-08T14:44:45Z
Abstract
This paper investigates the applicability of Genetic Programming type systems to dynamic game environments. Grammatical Evolution was used to evolve Behaviour Trees, in order to create controllers for the Mario AI Benchmark. The results obtained reinforce the applicability of evolutionary programming systems to the development of artificial intelligence in games, and in dynamic systems in general, illustrating their viability as an alternative to more standard AI techniques.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Springer
Copyright (Published Version)
2011 Springer
Subject – LCSH
Evolutionary computation
Genetic programming (Computer science)
Artificial intelligence
Video games
Web versions
Language
English
Status of Item
Peer reviewed
Journal
Di Chio, C. et al. [eds.]. Applications of Evolutionary Computation EvoApplications 2011: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, Torino, Italy, April 27-29, 2011, Proceedings, Part I
Conference Details
EvoGAMES 2011 3rd European Event on Bio-inspired Algorithms in Games in EvoApplications 2011, Torino, Italy, April, 2011
ISBN
978-3-642-20524-8
This item is made available under a Creative Commons License
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EvoGames2011_Perez.pdf
Size
363.91 KB
Format
Adobe PDF
Checksum (MD5)
d31faba5dbf7971cc59bbee45bf0d31b
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