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

Varunyu Vorachart, Hideyuki Takagi

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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
Volume13
Issue number6
Publication statusPublished - Dec 1 2017

Fingerprint

Fuzzy Logic
Fuzzy logic
Game
Fuzzy Logic System
Model
Video Games
Computational Intelligence
Differential Evolution Algorithm
Parameter Tuning
Evolutionary Computation
Membership functions
Differential Evolution
Membership Function
Evolutionary algorithms
Artificial intelligence
Tuning
Optimization
Experiment
Experiments
Framework

All Science Journal Classification (ASJC) codes

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

Cite this

Evolving fuzzy logic rule-based game player model for game development. / Vorachart, Varunyu; Takagi, Hideyuki.

In: International Journal of Innovative Computing, Information and Control, Vol. 13, No. 6, 01.12.2017, p. 1941-1951.

Research output: Contribution to journalArticle

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