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A Game Informatical Analysis of Dark Chess by Game Refinement Theory

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Science and Technologies for Smart Cities (SmartCity 360 2019)

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Abstract

This paper explores the evolutionary changes of Chinese chess variants such as Chinese dark chess. A computer program is created for each variant and self-play experiments are performed to collect many data such as the average number of possible moves and game length. These data are analyzed to examine the degree of game sophistication, while game refinement measure is employed for the assessment.

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Authors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Shuo Xiong

  2. Wuhan University, Wuhan, China

    Aoshuang Ye

  3. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Hiroyuki Iida

Authors
  1. Shuo Xiong
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  2. Aoshuang Ye
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  3. Hiroyuki Iida
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Corresponding author

Correspondence to Aoshuang Ye .

Editor information

Editors and Affiliations

  1. Information Systems Department, University of Minho, Guimaraes, Portugal

    Henrique Santos

  2. Department of E-Governance and Administration, Danube University Krems, Krems an der Donau, Niederösterreich, Austria

    Gabriela Viale Pereira

  3. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Matthias Budde

  4. University of Minho, Guimarães, Portugal

    Sérgio F. Lopes

  5. ShanghaiTech University, Shanghai, China

    Predrag Nikolic

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Xiong, S., Ye, A., Iida, H. (2020). A Game Informatical Analysis of Dark Chess by Game Refinement Theory. In: Santos, H., Pereira, G., Budde, M., Lopes, S., Nikolic, P. (eds) Science and Technologies for Smart Cities. SmartCity 360 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-030-51005-3_30

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  • DOI: https://doi.org/10.1007/978-3-030-51005-3_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51004-6

  • Online ISBN: 978-3-030-51005-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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