Finding Game Levels with the Right Difficulty in a Few Trials through Intelligent Trial-and-Error

Understand

Methods for dynamic difficulty adjustment allow games to be tailored to particular players to maximize their engagement.

• However, current methods often only modify a limited set of game features such as the difficulty of the opponents, or the availability of resources.
• Other approaches, such as experience-driven Procedural Content Generation (PCG), can generate complete levels with desired properties such as levels that are neither too hard nor too easy, but require many iterations.
• This paper presents a method that can generate and search for complete levels with a specific target difficulty in only a few trials.