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Abstract

Path-finding is an important problem for many applications, including network traffic, robot planning, military simulations, and computer games. Typically, a grid is superimposed over a region, and a graph search is used to find the optimal (minimal cost) path. The most common scenario is to use a grid of tiles and to search using A*. This paper discusses the tradeoffs for different grid representations and grid search algorithms. Grid representations discussed are 4-way tiles, 8-way tiles, and hexes. This paper introduces texes as an efficient representation of hexes. The search algorithms used are A* and iterative deepening A* (IDA*). Application-dependent properties dictate which grid representation and search algorithm will yield the best results.

Keywords

Computer Game Grid Search Hexagonal Grid Human Player Tile Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    K. Forbus, J. Mahoney, and K. Dill. How qualitative spatial reasoning can improve strategy game AIs. AAAI Spring Symposium on Artificial Intelligence and Interactive Entertainment, pages 35–40, 2001.Google Scholar
  2. 2.
    P. Hart, N. Nilsson, and B. Raphael. A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybernet., 4(2):100–107, 1968.CrossRefGoogle Scholar
  3. 3.
    S. Johnson. Wild Things. Wired, pages 78–83, 2002. March issue.Google Scholar
  4. 4.
    R. Korf. Depth-first iterative-deepening: An optimal admissible tree search. Artificial Intelligence, 27(1):97–109, 1985.zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    R. Korf, M. Reid, and S. Edelkamp. Time complexity of iterative-deepening A*. Artificial Intelligence, 129(2):199–218, 2001.zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    J. Laird and M. van Lent. Human-level AI’s killer application: Interactive computer games. In AAAI National Conference, pages 1171–1178, 2000.Google Scholar
  7. 7.
    J. Pearl. Heuristics: Intelligent search strategies. In Addison-Wesley, 1984.Google Scholar
  8. 8.
    S. Rabin. A* Aesthetic Optimizations. Game Programming Gems. Charles River Media, pages 264–271, 2000.Google Scholar
  9. 9.
    B. Stout. Smart moves: Intelligent path-finding. Game Developer Magazine, (October):28–35, 1996.Google Scholar
  10. 10.
    D. Takahashi. Games get serious. Red Herring, (87):64–70, 2000. December 18 issue.Google Scholar
  11. 11.
    P. Yap. New Ideas in Pathfinding. PhD thesis, Department of Computing Science, University of Alberta. In preparation.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Peter Yap
    • 1
  1. 1.Department of Computing ScienceUniversity of AlbertaEdmontonCanada

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