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Evolving Behaviour Trees for the Mario AI Competition Using Grammatical Evolution

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Applications of Evolutionary Computation (EvoApplications 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6624))

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Abstract

This paper investigates the applicability of Genetic Programming type systems to dynamic game environments. Grammatical Evolution was used to evolved 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.

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Author information

Authors and Affiliations

  1. Natural Computing Research & Applications Group, University College Dublin, Dublin, Ireland

    Miguel Nicolau, Michael O’Neill & Anthony Brabazon

Authors
  1. Diego Perez
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  2. Miguel Nicolau
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  3. Michael O’Neill
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  4. Anthony Brabazon
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  3. Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  4. Wilhelm-Schickard-Institut für Informatik, Universität Tübingen, Sand 1, 72076, Tübingen, Germany

    Marc Ebner

  5. Knowledge Engineering Research Group, Aston University, Aston Triangle, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna I. Esparcia-Alcázar

  7. Departamento de Electrónica y Tecnología de los Computadores, Universidad de Granada, 18071, Grenada, Spain

    Juan J. Merelo

  8. Department of Mathematical Information Technology, University of Jyväskylä, 4th Floor, P.O. Box 25, 40014, Agora, Finland

    Ferrante Neri

  9. Lehrstuhl für Algorithm Engineering, Technische Universität Dortmund, Otto-Hahn-Straße 14, 44227, Dortmund, Germany

    Mike Preuss

  10. Fakultät Elektrotechnik und Informationstechnik, HTWK Leipzig, Postfach 30 11 66, 04251, Leipzig, Germany

    Hendrik Richter

  11. Center for Computer Games Research, IT University of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen S, Denmark

    Julian Togelius  & Georgios N. Yannakakis  & 

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© 2011 Springer-Verlag Berlin Heidelberg

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Perez, D., Nicolau, M., O’Neill, M., Brabazon, A. (2011). Evolving Behaviour Trees for the Mario AI Competition Using Grammatical Evolution. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6624. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20525-5_13

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  • DOI: https://doi.org/10.1007/978-3-642-20525-5_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20524-8

  • Online ISBN: 978-3-642-20525-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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