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Machine Learning

, Volume 63, Issue 3, pp 211–215 | Cite as

Machine learning and games

  • Michael Bowling
  • Johannes Fürnkranz
  • Thore Graepel
  • Ron Musick
Guest Editorial
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References

  1. Aha, D. W., Muñoz-Avila H. M., & van Lent, M. (Eds.), (2005). Reasoning, representation, and learning in computer games: Proceedings of the IJCAI workshop. Edinburgh, Scotland: Naval Research Laboratory, Navy Center for Applied Research in Artificial Intelligence. Technical Report AIC-05-127.Google Scholar
  2. Billings, D., Peña, L., Schaeffer, J., & Szafron, D. (2002). The challenge of poker. Artificial Intelligence, 134(1–2), 201–240, Special Issue on Games, Computers and Artificial Intelligence.Google Scholar
  3. Bourg, D. M., & Seemann G. (2004). AI for game developers—Creating intelligent behavior in games. O’Reilly.Google Scholar
  4. Champanard, A. (2003). AI game development. New Riders Publishing.Google Scholar
  5. Collins, M. (2002). Advanced AI game development. Wordware Publishing Inc.Google Scholar
  6. Forbus, K. D., & Laird J. E. (2002). Guest editors’ introduction: AI and the entertainment industry. IEEE Intelligent Systems, 17(4), 15–16.CrossRefGoogle Scholar
  7. Fu, D. & Orkin J. (Eds.), (2004). Challenges of game AI: Proceedings of the AAAI-04 workshop. AAAI Press. Technical Report WS-04-04.Google Scholar
  8. Fürnkranz, J. (2001). Machine learning in games: A survey. In (Fürnkranz and Kubat, 2001), (pp. 11–59).Google Scholar
  9. Fürnkranz, J., & Kubat M. (Eds.), (2001). Machines that learn to play games. Huntington, NY: Nova Science Publishers.Google Scholar
  10. Ginsberg, M. L. (1998). Computers, games and the real world. Scientific American Presents 9:4. Special Issue on Exploring Intelligence/.Google Scholar
  11. Ginsberg, M. L. (1999). GIB: Steps toward an expert-level bridge-playing program. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-99), (pp. 584–589), Stockholm, Sweden.Google Scholar
  12. Laird, J. E., & van Lent, M. (2001). Human-level AI’s killer application: Interactive computer games. AI Magazine, 22(2), 15–26.Google Scholar
  13. Nunn, J. (1992). Secrets of rook endings. Batsford.Google Scholar
  14. Nunn, J. (1994a). Extracting information from endgame databases. In H. J. van den Herik, I. S. Herschberg, and J. W. H. M. Uiterwijk (Eds.), Advances in computer chess 7, (pp. 19–34). Maastricht, The Netherlands: University of Limburg.Google Scholar
  15. Nunn, J. (1994b). Secrets of pawnless endings. Batsford.Google Scholar
  16. Nunn, J. (1995). Secrets of minor-piece endings. Batsford.Google Scholar
  17. Rabin, S. (Ed.), (2002). AI game programming wisdom. Charles River Media.Google Scholar
  18. Rabin, S. (Ed.), (2003). AI game programming wisdom 2. Charles River Media.Google Scholar
  19. Rabin, S. (Ed.), (2006). AI game programming wisdom 3. Charles River Media.Google Scholar
  20. Samuel, A. L. (1959). Some studies in machine learning using the game of checkers. IBM Journal of Research and Development, 3(3), 211–229.MathSciNetGoogle Scholar
  21. Samuel, A. L. (1967). Some studies in machine learning using the game of checkers. II—Recent progress. IBM Journal of Research and Development, 11(6), 601–617.CrossRefGoogle Scholar
  22. Schaeffer, J. (2000). The games computers (and people) play. In M. V. Zelkowitz (Ed.), Advances in computers, vol. 50, (pp. 189–266). Academic Press.Google Scholar
  23. Schaeffer, J., & van den Herik, H. J. (Eds.), (2002). Chips challenging champions: Games, computers and artificial intelligence. North-Holland Publishing. Reprint of a Special Issue of Artificial Intelligence, 134(1–2).Google Scholar
  24. Schwab, B. (2004). AI game engine programming. Charles River Media.Google Scholar
  25. Spall, J. C. (1992). Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37, 332–341.MATHMathSciNetCrossRefGoogle Scholar
  26. Tesauro, G. (1995). Temporal difference learning and TD-Gammon. Communications of the ACM, 38(3), 58–68.CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • Michael Bowling
  • Johannes Fürnkranz
  • Thore Graepel
  • Ron Musick

There are no affiliations available

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