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Dynamic Game Level Generation Using On-Line Learning

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Technologies for E-Learning and Digital Entertainment (Edutainment 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4469))

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Abstract

In recent years, many researchers are attracted to computer games research. Capable gamers can easily get bored, while beginners tend to give up after trying several times because the game does not correspond to their level of interest. Therefore, this paper proposes that the user’s play pattern to be modeled on the basis of probability and level designer will dynamically generates the gaming level accordingly. We analyze user’s play pattern and design pattern based on GMM (probability model) and dynamically generate the level with online learning technique adapting the reinforcement technique. The play pattern is modeled using GMM and in order to create game level dynamically, the method of updating the weight of enemy creation using online script is proposed. Finally, we apply our proposed method to a 2D shooting game and introduce user’s play pattern leading to design pattern in the game.

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References

  1. Falstein, N.: Game Developer Magazine, The Flow Channel (2004)

    Google Scholar 

  2. Koster, R.: Theory of Fun for Game Design. Paraglyph Press, Phoenix (2004)

    Google Scholar 

  3. Johnson, D., Wiles, J.: Effective Affective User Interface Design in Games. In: International Conference on Affective Human Factors Design, Singapore (2003)

    Google Scholar 

  4. Laired, J.E.: Using a Computer Game to Develop Advanced AI, pp. 70–75. IEEE Computer Society Press, Los Alamitos (2001)

    Google Scholar 

  5. Freisleben, B.: A Neural Network that Learns to Play Five-in-a-Row. In: International Conference on Artificial Neural Networks and Expert Systems, pp. 87–90 (1995)

    Google Scholar 

  6. Faybish, I.: Applying the Genetic Algorithm to the Game of Othello, Master’s thesis, Vrije Universiteit Brussel, Computer Science Department, Brussels, Belgium (1999)

    Google Scholar 

  7. Moon, T.K.: The Expectation-Maximization Algorithm. IEEE Signal Processing 13, 47–60 (1996)

    Article  Google Scholar 

  8. Carson, C., Belongie, S., Greenspan, H., Malik, J.: Blobword: Image Segmentaion Using Expectation-Maximization and Its Application to Image Querying. IEEE Trans. On Pattern Recognition and Machine Analysis 24(8), 1026–1038 (2002)

    Article  Google Scholar 

  9. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. p. 55. John Wiley & Sons Inc, Chichester (2001)

    MATH  Google Scholar 

  10. Ghory, I.: Reinforcement learning in board games, Technical Report CSTR-04-004, Department of Computer Science, University of Bristol, (May 2004)

    Google Scholar 

  11. Spronck, P., Sprinkhuizen-Kuyper, I., Postma, E.: Difficulty Scaling of Game AI. In: International Conference on Intelligent Games and Simulation, Belgium, pp. 33–37 (2004)

    Google Scholar 

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Authors and Affiliations

Authors

Editor information

Kin-chuen Hui Zhigeng Pan Ronald Chi-kit Chung Charlie C. L. Wang Xiaogang Jin Stefan Göbel Eric C.-L. Li

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© 2007 Springer Berlin Heidelberg

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Yang, J., Min, S., Wong, CO., Kim, J., Jung, K. (2007). Dynamic Game Level Generation Using On-Line Learning. In: Hui, Kc., et al. Technologies for E-Learning and Digital Entertainment. Edutainment 2007. Lecture Notes in Computer Science, vol 4469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73011-8_88

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  • DOI: https://doi.org/10.1007/978-3-540-73011-8_88

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73010-1

  • Online ISBN: 978-3-540-73011-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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