Evolving behaviour trees for the Mario AI competition using grammatical evolution

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Title: Evolving behaviour trees for the Mario AI competition using grammatical evolution
Authors: Perez, Diego
Nicolau, Miguel
O'Neill, Michael
Brabazon, Anthony
Permanent link: http://hdl.handle.net/10197/3534
Date: 27-Apr-2011
Online since: 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.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Copyright (published version): 2011 Springer
Keywords: Grammatical evolutionBehaviour treesMarioAI competition
Subject LCSH: Evolutionary computation
Genetic programming (Computer science)
Artificial intelligence
Video games
DOI: 10.1007/978-3-642-20525-5_13
Other versions: http://dx.doi.org/10.1007/978-3-642-20525-5_13
Language: en
Status of Item: Peer reviewed
Is part of: 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
Appears in Collections:Computer Science Research Collection
CASL Research Collection

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