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Game-Playing Agents and Non-player Characters

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Computational Models of Motivation for Game-Playing Agents

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Abstract

This chapter brings together the background and theory from the previous two chapters in four agent architectures for game-playing agents.

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References

  1. Spore (Maxis 2008), www.spore.com

  2. D. Acemoglu, M. Yildiz, Evolution of perceptions and play. Massachusetts Institute of Technology, Department of Economics, Working Paper 01-36 (2001)

    Google Scholar 

  3. T. Borgers, R. Sarin, Learning through reinforcement and replicator dynamics. J. Econ. Theory 77, 1–14 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  4. A. Colman, Game Theory and Experimental Games: The Study of Strategic Interaction (Pergamon Press, Oxford, England, 1982)

    Google Scholar 

  5. E. Dekel, J. Ely, O. Ylankaya, Evolution of preferences. Rev. Econ. Stud. 74, 685–704 (2007)

    MathSciNet  MATH  Google Scholar 

  6. P. Fishburn, Lexicographic orders, utilities and decision rules: a survey. Manag. Sci. 20, 1442–1471 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  7. G. Gigerenzer, P. Todd, Simple Heuristics That Make us Smart (Oxford University Press, NY, 1999)

    Google Scholar 

  8. D. Goldberg, Genetic Algorithms in Search, Optimisation and Machine Learning (Addison-Wesley Professional, Reading, MA, 1989)

    MATH  Google Scholar 

  9. T. Graepel, R. Herbrich, J. Gold, Learning to fight, in Proceedings of the International Conference on Computer Games: Artificial Intelligence, Design and Education (2004)

    Google Scholar 

  10. J. Graham, J. Starzyk, D. Jachyra, Opportunistic behavior in motivated learning agents. IEEE Trans. Neural Netw. Learn. Syst. 26, 1735–1746 (2014)

    Article  MathSciNet  Google Scholar 

  11. S. Grand, Creation: Life and How To Make It (Harvard University Press, 2003)

    Google Scholar 

  12. O. Guillermo, Game Theory (Academic Press, San Diego, CA, 1995)

    MATH  Google Scholar 

  13. E. Hastings, R. Guha, K. Stanley, Evolving content in the Galactic Arms Race video game, in Proceedings of the IEEE Symposium on Computational Intelligence in Games (Milano, 2009), pp. 241–248

    Google Scholar 

  14. E. Hastings, R. Guha, K. Stanley, Automatic content generation in the Galactic Arms Race video game. IEEE Trans. Comput. Intell. AI Games 1, 245–263 (2009)

    Article  Google Scholar 

  15. J. Heckhausen, H. Heckhausen, Motivation and Action (Cambridge University Press, New York, NY, 2010)

    Google Scholar 

  16. D. Kahneman, A. Tversky, Prospect theory: an analysis of decision under risk. Econometrica 47, 263–292 (1979)

    Article  MATH  Google Scholar 

  17. R.L. Keeney, H. Raiffa, Decisions with Multiple Objectives: Preferences and Value Tradeoffs (Wiley, New York, 1976)

    MATH  Google Scholar 

  18. D. Kehoe, Designing artificial intelligence for games (part 1) (2012), https://software.intel.com/en-us/articles/designing-artificial-intelligence-for-games-part-1. Accessed 27 Aug 2014

  19. M. Mateas, Expressive AI: games and artificial intelligence, in Proceedings of the Level Up: Digital Games Research Conference (Utrecht, Netherlands, 2003)

    Google Scholar 

  20. S. Meier, Civilization (2K Games, 1991), http://www.civilization.com/en/home

  21. K. Merrick, M.L. Maher, Motivated Reinforcement Learning: Curious Characters for Multiuser Games (Springer-Verlag, Berlin, 2009)

    Book  Google Scholar 

  22. K. Merrick, The role of implicit motives in strategic decision-making: computational models of motivated learning and the evolution of motivated agents. Games 6, 604–636 (2015). (Special Issue on Psychological Aspects of Strategic Choice)

    Article  MathSciNet  Google Scholar 

  23. Microsoft, Drivatar in Forza Motorsport (2014), http://research.microsoft.com/en-us/projects/drivatar/forza.aspx. Accessed 31 Oct 2014

  24. N.J. Nilsson, Introduction to machine learning (1996), http://ai.stanford.edu/people/nilsson/mlbook.html. Accessed Jan 2006

  25. M. Nowak, Evolutionary dynamics: exploring the equations of life (Belknap Press, Canada, 2006)

    MATH  Google Scholar 

  26. C.W. Reynolds, Flocks, herds and schools: a distributed behavioral model. Comput. Gr. 21, 25–34 (1987). (SIGGRAPH 87 Conference Proceedings)

    Article  Google Scholar 

  27. R. Saunders, J.S. Gero, Curious agents and situated design evaluations. Artif. Intell. Eng. Des. Anal. Manuf. 18, 153–161 (2004)

    Article  Google Scholar 

  28. G. Seemann, D. Bourg, AI for Game Developers (O’Reilly Media Inc, 2004)

    Google Scholar 

  29. K. Stanley, R. Cornelius, R. Miikkulainen, T. D’Silva, A. Gold, Real-time learning in the NERO video game, in Proceedings of the Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (2005)

    Google Scholar 

  30. K. Stanley, I. Karpov, R. Miikkulainen, A. Gold, The NERO video game, in Proceedings of the Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (2006), pp. 151–152

    Google Scholar 

  31. J. Von Neumann, O. Morgenstern, Theory of Games and Economic Behavior (Princeton University Press, Princeton, NJ, 1953)

    MATH  Google Scholar 

  32. M. Wang, K. Hipel, N. Fraser, Modeling misperceptions in games. Behav. Sci. 33, 207–223 (1988)

    Article  MathSciNet  Google Scholar 

  33. G. Yannakakis, Game AI revisited, in Proceedings of the Ninth Conference on Computing Frontiers, (Cagliari, Italy, 2012), pp. 285–292

    Google Scholar 

  34. N. Yee, Motivations of play in online games. Cyberpsychol. Behav. 9, 772–775 (2007)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales Australian Defence Force Academy, Canberra, ACT, Australia

    Kathryn E. Merrick

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  1. Kathryn E. Merrick
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Correspondence to Kathryn E. Merrick .

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Merrick, K.E. (2016). Game-Playing Agents and Non-player Characters. In: Computational Models of Motivation for Game-Playing Agents. Springer, Cham. https://doi.org/10.1007/978-3-319-33459-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-33459-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33457-8

  • Online ISBN: 978-3-319-33459-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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