Dynamic Difficulty Adjustment in 2D Platformers through Agent-Based Procedural Level Generation

The rapid growth of the entertainment industry has driven the requirement for more efficient development of computerized games. Importantly, the diversity of audiences that participate in playing games has called for the development of new technologies that allow games to address users with differing levels of skills and preferences. This study explored the application of dynamic difficulty adjustment in computerized 2D plat former games through procedural level generation and interactive evolutionary computation. Computerized agents were introduced into the evolutionary cycle to play game levels in the player´s stead. Additionally, agent behavior was based on the player´s game-play characteristics, which has provided a more practical means for evaluating and evolving game levels tailored to a particular player´s skills.