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Pathfinding Strategy for Multiple Non-Playing Characters in 2.5 D Game Worlds

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Learning by Playing. Game-based Education System Design and Development (Edutainment 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5670))

Abstract

This paper investigates and determines the optimal pathfinding strategy for non-playing characters (NPCs) in 2.5D game worlds. Three algorithms, Dijkstra’s, Best-first Search (BFS) and the A* algorithm using Manhattan distance, Euclidean distance and Diagonal distance heuristics, are tested under different interaction schemes and test environments consisting of different levels of obstacles. The result shows that the A* algorithm is the optimal algorithm under the Manhattan distance Heuristic. Our tests did not reveal significant difference among the cooperative, non-cooperative or competitive interaction schemes.

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References

  1. Dijkstra, E.W.: A Note on Two Problems in Connexion with Graphs. Numerische Mathematik 1(1), 269–271 (1959), http://dx.doi.org/10.1007/BF01386390

    Article  MathSciNet  MATH  Google Scholar 

  2. Morris, J.: Data Structures and Algorithms: Dijkstra’s Algorithm, http://www.cs.auckland.ac.nz/software/AlgAnim/dijkstra.html

  3. Wichmann, D.R., Wuensche, B.C.: Automated Route Finding on Digital Terrains. In: Proceedings of IVCNZ 2004, Akaroa, New Zealand, pp. 107–112 (2004)

    Google Scholar 

  4. Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs (1995)

    MATH  Google Scholar 

  5. Hart, P.E., Nilsson, N.J., Raphael, B.: A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions on Systems Science & Cybernetics 4(2), 100–107 (1968), http://dx.doi.org/10.1109/TSSC.1968.300136

    Article  Google Scholar 

  6. Matthews, J.: Basic A* Pathfinding Made Simple. In: Rabin, S. (ed.) AI Game Programming Wisdom, pp. 105–113. Charles River Media, Inc., Rockland (2002)

    Google Scholar 

  7. Goodrich, M.T., Tamassia, R.: Data Structures and Algorithms in Java, 3rd edn. John Wiley & Sons, Inc., Chichester (2004)

    MATH  Google Scholar 

  8. Silver, D.: Cooperative pathfinding. In: Proceedings of the First Artificial Intelligence and Interactive Digital Entertainment conference, pp. 117–122. AAAI Press, Menlo Park (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Athabasca University, 1 University Drive, Athabasca, AB, T9S 3A3, Canada

    Jason MacGregor & Steve Leung

Authors
  1. Jason MacGregor
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  2. Steve Leung
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Editor information

Editors and Affiliations

  1. School of Computing and Information Systems 1200, Athabasca University, 10011-109 Street, T5J-3S8, Edmont, Canada

    Maiga Chang

  2. Department of Digital Design 369, Ming Dao University, Wen-Hua Dr., Peetow, 52345, ChangHua, Taiwan

    Rita Kuo

  3. School of Computing and Inforamtion Systems, Athabasca University, 1 University Drive, T9S 3A3, Athabasca, AB, Canada

    Kinshuk

  4. Department of Computer Science and Information Engineering, National Central University, 300, Jhongda Rd., 32001, Jhongli City, Taiwan

    Gwo-Dong Chen

  5. Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, 113-8656, Tokyo, Japan

    Michitaka Hirose

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© 2009 Springer-Verlag Berlin Heidelberg

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MacGregor, J., Leung, S. (2009). Pathfinding Strategy for Multiple Non-Playing Characters in 2.5 D Game Worlds. In: Chang, M., Kuo, R., Kinshuk, Chen, GD., Hirose, M. (eds) Learning by Playing. Game-based Education System Design and Development. Edutainment 2009. Lecture Notes in Computer Science, vol 5670. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03364-3_43

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  • DOI: https://doi.org/10.1007/978-3-642-03364-3_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03363-6

  • Online ISBN: 978-3-642-03364-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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