Modeling player-like behavior for game AI design

  • Authors:
  • David Conroy;Peta Wyeth;Daniel Johnson

  • Affiliations:
  • QLD University of Technology, Brisbane, QLD, Australia;QLD University of Technology, Brisbane, QLD, Australia;QLD University of Technology, Brisbane, QLD, Australia

  • Venue:
  • Proceedings of the 8th International Conference on Advances in Computer Entertainment Technology
  • Year:
  • 2011

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Abstract

The design of artificial intelligence in computer games is an important component of a player's game play experience. As games are becoming more life-like and interactive, the need for more realistic game AI will increase. This is particularly the case with respect to AI that simulates how human players act, behave and make decisions. The purpose of this research is to establish a model of player-like behavior that may be effectively used to inform the design of artificial intelligence to more accurately mimic a player's decision making process. The research uses a qualitative analysis of player opinions and reactions while playing a first person shooter video game, with recordings of their in-game actions, speech and facial characteristics. The initial studies provide player data that has been used to design a model of how a player behaves.