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Spotting the Difference: Identifying Player Opponent Preferences in FPS Games

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7522)

Abstract

This paper describes a study designed to understand player responses to artificially intelligent opponents in multi-player First Person Shooter games. It examines the player’s ability to tell the difference between artificially intelligent opponents and other human players, and investigates the players’ perceptions of these opponents. The study examines player preferences in this regard and identifies the significance of the cues and signs players use to categorise an opponent as artificial or human.

Keywords

  • Video Games
  • Artificial Intelligence
  • Indentification Processes
  • User Study
  • Multi-player

References

  1. Hingston, P.: A Turing Test for Computer Game Bots. IEEE Transactions on Computational Intelligence and AI in Games 1, 169–186 (2009)

    CrossRef  Google Scholar 

  2. Esparcia-alc, A.I., Member, S., Mora, A., Merelo, J.J., Garc, P.: Controlling bots in a First Person Shooter Game using Genetic Algorithms. Environment (2010)

    Google Scholar 

  3. Conroy, D., Wyeth, P., Johnson, D.: Modeling player-like behavior for game AI design. In: Proceedings of the 8th International Conference on Advances in Computer Entertainment Technology - ACE 2011, p. 1. ACM Press, New York (2011)

    Google Scholar 

  4. Weibel, D., Wissmath, B., Habegger, S., Steiner, Y., Groner, R.: Playing online games against computer- vs. human-controlled opponents: Effects on presence, flow, and enjoyment. Computers in Human Behavior. 24, 2274–2291 (2008)

    CrossRef  Google Scholar 

  5. Hartley, T.P., Mehdi, Q.H.: In-game tactic adaptation for interactive computer games. In: 16th International Conference on Computer Games (CGAMES 2011), pp. 41–49 (2011)

    Google Scholar 

  6. Clarke, D., Duimering, P.R.: How computer gamers experience the game situa-tion: a behavioral study. Computers in Entertainment 4, 6 (2006)

    CrossRef  Google Scholar 

  7. Przybylski, A.K., Rigby, C.S., Ryan, R.M.: A motivational model of video game engagement. Review of General Psychology 14, 154–166 (2010)

    CrossRef  Google Scholar 

  8. Rayner, C.: Player Modelling for Cursor-Driven Games. Challenges (2007)

    Google Scholar 

  9. Laird, J.E.: Using a computer game to develop advanced AI. Computer 34, 70–75 (2001)

    CrossRef  Google Scholar 

  10. Krach, S., Blümel, I., Marjoram, D., Lataster, T., Krabbendam, L., Weber, J., van Os, J., Kircher, T.: Are women better mindreaders? Sex differences in neural correlates of mentalizing detected with functional MRI. BMC Neuroscience 10, 9 (2009)

    CrossRef  Google Scholar 

  11. Conroy, D., Wyeth, P.: Building Better Bad Guys: A New Framework for Game AI Design. In: Proceedings of the 7th Australasian Conference on Interactive Entertainment, IE 2010, pp. 0–2. ACM Press (2010)

    Google Scholar 

  12. Bushnell, D., Irwin, M.: Observational Strategies for Child Study. Rinehart and Winston, Holt (1980)

    Google Scholar 

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Conroy, D., Wyeth, P., Johnson, D. (2012). Spotting the Difference: Identifying Player Opponent Preferences in FPS Games. In: Herrlich, M., Malaka, R., Masuch, M. (eds) Entertainment Computing - ICEC 2012. ICEC 2012. Lecture Notes in Computer Science, vol 7522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33542-6_10

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  • DOI: https://doi.org/10.1007/978-3-642-33542-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33541-9

  • Online ISBN: 978-3-642-33542-6

  • eBook Packages: Computer ScienceComputer Science (R0)