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Clustering-Based Online Player Modeling

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Computer Games (CGW 2016, GIGA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 705))

Abstract

Being able to imitate individual players in a game can benefit game development by providing a means to create a variety of autonomous agents and aid understanding of which aspects of game states influence game-play. This paper presents a clustering and locally weighted regression method for modeling and imitating individual players. The algorithm first learns a generic player cluster model that is updated online to capture an individual’s game-play tendencies. The models can then be used to play the game or for analysis to identify how different players react to separate aspects of game states. The method is demonstrated on a tablet-based trajectory generation game called Space Navigator.

M.E. Miller—The views expressed in this document are those of the author and do not reflect the official policy or position of the United States Air Force, the United States Department of Defense, or the United States Government. This work was supported in part through the Air Force Office of Scientific Research, Computational Cognition & Robust Decision Making Program (FA9550), James Lawton Program Manager.

The rights of this work are transferred to the extent transferable according to title 17 § 105 U.S.C.

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Authors and Affiliations

  1. Air Force Institute of Technology, Wright-Patterson AFB, OH, USA

    Jason M. Bindewald, Gilbert L. Peterson & Michael E. Miller

Authors
  1. Jason M. Bindewald
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  2. Gilbert L. Peterson
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  3. Michael E. Miller
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Corresponding author

Correspondence to Gilbert L. Peterson .

Editor information

Editors and Affiliations

  1. LAMSADE, Université Paris-Dauphine, Paris Cedex 16, France

    Tristan Cazenave

  2. Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Limburg, The Netherlands

    Mark H.M. Winands

  3. Institute for Artificial Intelligence, Universität Bremen, TAB, Bremen, Bremen, Germany

    Stefan Edelkamp

  4. Reykjavik University, Reykjavik, Iceland

    Stephan Schiffel

  5. The University of New South Wales, Sydney, New South Wales, Australia

    Michael Thielscher

  6. Department of Computer Science and Engineering, New York University, Brooklyn, New York, USA

    Julian Togelius

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Bindewald, J.M., Peterson, G.L., Miller, M.E. (2017). Clustering-Based Online Player Modeling. In: Cazenave, T., Winands, M., Edelkamp, S., Schiffel, S., Thielscher, M., Togelius, J. (eds) Computer Games. CGW GIGA 2016 2016. Communications in Computer and Information Science, vol 705. Springer, Cham. https://doi.org/10.1007/978-3-319-57969-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-57969-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57968-9

  • Online ISBN: 978-3-319-57969-6

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