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Using Ants’ Task Division for Better Game Engines – A Contribution to Game Accessibility for Impaired Players

  • Alexis Sepchat
  • Romain Clair
  • Nicolas Monmarché
  • Mohamed Slimane
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)

Abstract

Designing a relevant artificial intelligence engine for video games does not always consist in finding the best solution (best opponent, best path, etc.): it can sometimes consist in offering the player the best gaming experience. Such a good experience is linked with the difficulty level of the proposed challenge. A game that is too easy will be boring whereas a game that is too difficult will be stressful. So, to be interesting for everyone, an artificial intelligence engine should provide an adaptive game level for every player. This game tuning is particularly prominent in the especial case of accessible games for impaired player. In this paper we show that the task division model based on ant colonies can be an interesting way to provide adaptive behaviors in game engines for simple one-player games.

Keywords

Computer Game Stimulus Intensity Task Allocation Response Threshold Level Problem 
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 2008

Authors and Affiliations

  • Alexis Sepchat
    • 1
  • Romain Clair
    • 1
  • Nicolas Monmarché
    • 1
  • Mohamed Slimane
    • 1
  1. 1.Laboratoire d’Informatique de l’Université François Rabelais de ToursÉquipe Handicap et Nouvelles Technologies (HaNT)France

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