Representing dynamic difficulty in turn-based role playing games using Monte Carlo tree search

Hafiz Adhiyasa Pratama, Adila Alfa Krisnadhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

One of the challenges during game development is to find a way on how to make the players actually enjoy the game itself while being quite hooked by its gameplay. In almost in every game, player must play the game through challenges to complete the game's main objectives. Enjoyment is highest when the game's challenges, which are either hard-coded or adaptively put forth by AI, are of appropriate difficulty with respect to the player's skill. In order to balance out between these two aspects, a difficulty adjustment is needed. In this paper, we study an application of Monte Carlo Tree Search (MTCS) for creating such a balancing using role playing games as the case study. The key idea is the intuition that a game's difficulty is balanced if any of the player or the AI can win or lose the game by only a small margin. We conduct experiment to see if the method is appropriate for this problem.

Original languageEnglish
Title of host publication2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages207-212
Number of pages6
ISBN (Electronic)9781728101354
DOIs
Publication statusPublished - 17 Jan 2019
Event10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 - Yogyakarta, Indonesia
Duration: 27 Oct 201828 Oct 2018

Publication series

Name2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018

Conference

Conference10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
CountryIndonesia
CityYogyakarta
Period27/10/1828/10/18

Keywords

  • Dynamic difficulty adjustment
  • Monte Carlo methods
  • Role playing game

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    Pratama, H. A., & Krisnadhi, A. A. (2019). Representing dynamic difficulty in turn-based role playing games using Monte Carlo tree search. In 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 (pp. 207-212). [8618167] (2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACSIS.2018.8618167