Abstract:
A method of maintaining player enjoyment in video games is by automatically matching its challenge level with the player's skill, also known as Dynamic Game Balancing (DGB). This systematic review aims to present a comprehensive overview regarding the characteristics of the game prototypes using DGB, as well as the variety of DGB algorithms utilized and their evaluated impact on player satisfaction. Following the PRISMA framework, 7 scholarly databases were searched between December 2023 and January 2024 to be filtered for publications discussing DGB implementation within the past 5 years. After excluding duplicate titles, unretrievable papers, and those irrelevant to DGB implementation, 91 papers were selected for full-text analysis. Many different categorized characteristics were studied in every paper, which covers the game prototype architectures, gameplay design, DGB systems, and testing results. It should be noted that some bias and inconsistency within the classification processes may exist due to potentially overgeneralizing the convoluted intricacies within the game and its DGB systems. Results show that development in DGB has expanded to many game types, purposes, and technologies. They leverage a multitude of algorithms and techniques to effectively measure player proficiency and modify the game's difficulty in various methods which leads to an overall better player satisfaction compared to non-DGB games. This review helps readers and potential game developers to better understand the current trends and patterns in DGB innovations that contribute to better adaptive gameplay and user experience in video games.
