Dynamic difficulty adjustment in digital games using genetic algorithms

Weber M.; Notargiacomo P.

Dynamic difficulty adjustment in digital games using genetic algorithms

Tipo

Artigo de evento

Data de publicação

2020

Periódico

Brazilian Symposium on Games and Digital Entertainment, SBGAMES

Citações (Scopus)

10

Autores

Weber M.
Notargiacomo P.

Resumo

© 2020 IEEEThe difficulty of a game is intrinsically connected with the experience of immersion in it and with its success. One of the main reasons for a player to drop a game is that the game is either too easy or too hard for him/her. In practice, players become either bored or frustrated if playing a game that is not balanced for them. An approach to prevent this kind of behavior is to dynamically adjust the difficulty of a game so that the game adapts to the player's experience by evaluating the difficulty of a game and changing its environment to become easier or harder for the player. In this paper, we propose a real-time solution using a Genetic Algorithm which helps to provide the exact amount of challenge that a player needs to not be bored or frustrated thus balancing the difficulty of a game. We review several other papers that approached this problem, which characteristics an algorithm has to have to approach the problem, and how to balance this in a generic way. The main idea of this paper is to create an approach that can be modified and coupled to any kind of game by using a Genetic Algorithm.

Assuntos Scopus

Digital games , Real time solution