Proceedings of the 1st International Conference on Informatics, Engineering, Science and Technology, INCITEST 2019, 18 July 2019, Bandung, Indonesia

Research Article

Can we save near-dying games? An approach using advantage of initiative and game refinement measures

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  • @INPROCEEDINGS{10.4108/eai.18-7-2019.2287539,
        author={Htun Pa Pa Aung and Mohd Nor Akmal Khalid},
        title={Can we save near-dying games? An approach using advantage of initiative and game refinement measures},
        proceedings={Proceedings of the 1st International Conference on Informatics, Engineering, Science and Technology, INCITEST 2019, 18 July 2019, Bandung, Indonesia},
        publisher={EAI},
        proceedings_a={INCITEST},
        year={2019},
        month={10},
        keywords={refinement games atificial intelligence},
        doi={10.4108/eai.18-7-2019.2287539}
    }
    
  • Htun Pa Pa Aung
    Mohd Nor Akmal Khalid
    Year: 2019
    Can we save near-dying games? An approach using advantage of initiative and game refinement measures
    INCITEST
    EAI
    DOI: 10.4108/eai.18-7-2019.2287539
Htun Pa Pa Aung1,*, Mohd Nor Akmal Khalid1
  • 1: School of Information Science, Japan Advanced Institute of Science and Technology
*Contact email: htun.pp.aung@jaist.ac.jp

Abstract

Games are attractive and engaging due to the complexity they pose to the player. Some games are complex enough which made them attractive to play. However, popular games would lose their attractiveness due to the large advantage of initiative. High-performance AI like AlphaZero suggests from their actual games played that advantage of the first player would become larger as the performance level increases. This implies that games with a large advantage of the initiative would lose their attractiveness due to the unfairness. This paper explores an innovative way to make a game stay attractive. A link between the advantage of initiative and performance level is investigated while using Scrabble AI. Using two measures: the advantage of initiative and game refinement, possible treatments are considered. The experimental results with Scrabble AI suggest that reduction of search space from 15x15 to 13x13 board size is a possible enhancement.