Evolving fuzzy logic rule-based game player model for game development

Varunyu Vorachart, Hideyuki Takagi

    Research output: Contribution to journalArticlepeer-review

    8 Citations (Scopus)


    We propose a framework for automatic game parameter tuning using a game player model. Two kinds of computational intelligence techniques are used to create the framework: a fuzzy logic system (FS) as the decision maker and evolutionary computation as the model parameter optimizer. Insights from a game developer are integrated into the player model consisting of FS rules. FS membership function parameters are optimized by a differential evolution (DE) algorithm to find optimal model parameters. We conducted experiments in which our player model plays a turn-based strategy video game. DE optimization was able to evolve our player model such that it could compete well at various levels of game difficulty.

    Original languageEnglish
    Pages (from-to)1941-1951
    Number of pages11
    JournalInternational Journal of Innovative Computing, Information and Control
    Issue number6
    Publication statusPublished - Dec 1 2017

    All Science Journal Classification (ASJC) codes

    • Software
    • Theoretical Computer Science
    • Information Systems
    • Computational Theory and Mathematics


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