Decision Tree-Based Algorithms for Implementing Bot AI in UT2004

  • Antonio J. Fernández Leiva
  • Jorge L. O’Valle Barragán
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6686)


This paper describes two different decision tree-based approaches to obtain strategies that control the behavior of bots in the context of the Unreal Tournament 2004. The first approach follows the traditional process existing in commercial videogames to program the game artificial intelligence (AI), that is to say, it consists of coding the strategy manually according to the AI programmer’s experience with the aim of increasing player satisfaction. The second approach is based on evolutionary programming techniques and has the objective of automatically generating the game AI. An experimental analysis is conducted in order to evaluate the quality of our proposals. This analysis is executed on the basis of two fitness functions that were defined intuitively to provide entertainment to the player. Finally a comparison between the two approaches is done following the subjective evaluation principles imposed by the “2k bot prize” competition.


Gaming Experience Genetic Programming Algorithm Genetic Programming Approach First Person Shooter Standard Genetic Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Antonio J. Fernández Leiva
    • 1
  • Jorge L. O’Valle Barragán
    • 1
  1. 1.Dept. Lenguajes y Ciencias de la Computación, ETSI InformáticaCampus de Teatinos, Universidad de MálagaMálagaSpain

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