JournalQ2GamesSimulation

Finding appropriate settings for fairness and engagement in a newly designed game through self-playing AI program: A case study using japanese crossword game extquotesingleMyoGo renju'

Xinyue, Liu and Luping, Fu and Khalid, M. N. A. and Iida, Hiroyuki

Entertainment Computing · vol. 34 · pp. 100358 · 2020

Interactive demo

Game refinement · self-play

DEMO

This interactive is a faithful re-design of the research, simplified for illustrative and teaching purposes. It conveys the idea and behaviour of the model — it is not the paper’s full method, data, or results.

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A looping preview of game-refinement theory: an abstract game plays itself, and its refinement value GR = √B ⁄ D settles on the engagement spectrum against the comfortable zone, with live thrill and addiction readouts.

Chicago citation

Xinyue, Liu and Luping, Fu and Khalid, M. N. A. and Iida, Hiroyuki. “Finding appropriate settings for fairness and engagement in a newly designed game through self-playing AI program: A case study using japanese crossword game  extquotesingleMyoGo renju'.” Entertainment Computing 34 (2020): 100358. https://doi.org/10.1016/j.entcom.2020.100358

BibTeX

@article{xinyue2020finding,
  author  = {Xinyue, Liu and Luping, Fu and Khalid, M. N. A. and Iida, Hiroyuki},
  title   = {Finding appropriate settings for fairness and engagement in a newly designed game through self-playing AI program: A case study using japanese crossword game  extquotesingleMyoGo renju'},
  journal = {Entertainment Computing},
  volume  = {34},
  pages   = {100358},
  year    = {2020},
  doi     = {10.1016/j.entcom.2020.100358},
}