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International Journal of Computer Games Technology
Volume 2008 (2008), Article ID 834616, 6 pages
http://dx.doi.org/10.1155/2008/834616
Research Article

Strategic Team AI Path Plans: Probabilistic Pathfinding

1School of Computer Engineering, Nanyang Technological University, Singapore 639798
2Department of Computing and Mathematics, Manchester Metropolitan University, Manchester M1 5GD, UK

Received 29 September 2007; Accepted 13 December 2007

Academic Editor: Kok Wai Wong

Copyright © 2008 Tng C. H. John et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. T. C. H. John, E. C. Prakash, and N. S. Chaudhari, “Team AI: probabilistic pathfinding,” in Proceedings of the International Conference on Game Research and Development, vol. 223 of ACM International Conference Proceeding, pp. 191–198, Perth, Australia, December 2006.
  2. S. Rabin, AI Game Programming Wisdom 2, Charles River Media, Hingham, Mass, USA, 2004.
  3. M. Buckland, Programming Game AI by Example, Wordware, Plano, Tex, USA, 2005.
  4. D. M. Bourg and G. Seeman, AI for Game Developers, O'Reilly, Sebastopol, Calif, USA, 2004.
  5. M. Pinter, “Gamasutra,” http://www.gamasutra.com/features/20010314/pinter_01.htm.
  6. A. Kamphuis, M. Rook, and M. H. Overmars, “Tactical path finding in urban environments,” 2005, http://www.cs.uu.nl/centers/give/movie/index.php.
  7. S. J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, Englewood Cliffs, NJ, USA, 2002.
  8. D. B. West, Introduction to Graph Theory, Prentice Hall, Upper Saddle River, NJ, USA, 2nd edition, 2000.