A Novel Multidimensional Dynamic Difficulty Adjustment Algorithm: Use Case in a Cognitive Training Video Game

This study introduces a novel methodological framework for cognitive control training, embedded in a video game that incorporates action-based gameplay and a multidimensional Dynamic Difficulty Adjustment (DDA) system. This system adapts to individual player performance in real-time, ensuring a personalized and engaging experience. The game architecture is modular, including a configurable set of cognitive training modules which are tailored according to one’s training goals. Transitioning between modules occurs through an action-based central hub following the literature on action video games and their positive impact on brain plasticity. Analysis of data from 34 players demonstrates how they progress through each module, with most players reaching their zone of proximal development after approximately 30-45 minutes of playing a module. Once players stabilize in their skill progression, the DDA system maintains variability in gameplay, a feature that has been suggested to promote the transfer of skills to novel situations. This analysis also highlights how our novel multidimensional DDA system accommodates a wide range of skill levels, offering a seamless on-boarding experience across a variety of players. Together, this novel architecture and DDA framework provide a new, rigorous methodological blueprint for the design of computerized cognitive training tools.