Solutions for dynamic difficulty adjustment in digital games: a systematic literature review

Abstract

Dynamic Difficulty Adjustment (DDA) is an important aspect of game design aimed at balancing the difficulty level to enhance player experience and prevent frustration or game abandonment. This paper presents a Systematic Literature Review (SLR) that focuses on the implementation of DDA techniques in digital games. The objective of this study was to identify and analyze DDA solutions (models, methods, and/or frameworks) for digital games in the ongoing research agenda. Of the 547 studies found in four bibliographic databases (ACM, IEEE, Scopus, and Web of Science), 34 were selected. The results revealed a diversity of approaches, mainly involving Artificial Intelligence techniques (50%) and heuristics/parameters manipulation (47%), among other possibilities. In addition to reaffirming the open research problems described in the literature, the need for further research on generalizable, flexible, and modularized approaches is highlighted, allowing the integration of various DDA strategies while minimizing the disadvantages of each strategy and ensuring good results. In this sense, the conducted review brings solution directions based on the exchange of knowledge from self-adaptive systems.