Dynamic Difficulty Adjustment via Dynamic Scripting: An Empirical Study of Player Flow in a Brawler Game

Abstract

Getting the level of challenge right in action games has always been difficult, especially in fast-moving titles where player skill can vary sharply from one person to the next. Fixed difficulty options rarely adjust well to how someone is actually performing in the moment. To explore a more responsive solution, we created a side-scrolling brawler in Unity with two different enemy control setups: one powered by real-time adaptive scripting and another built around a standard, non-adaptive AI. In the adaptive version, enemy actions shifted in priority based on the outcome of earlier encounters, while the underlying finite state machine remained unchanged so that behavior changes felt consistent rather than erratic. The study used a quasi-experimental setup with 42 participants recruited online. Each person filled out a short survey before playing, completed one version of the game, and then responded to a follow-up questionnaire focused on attention, perceived difficulty, and immersion. This approach made it possible to see how players responded as enemy behavior gradually changed during a single play session. The results show how dynamic scripting behaves in a fast-paced game with constant enemy encounters and how players respond when the difficulty shifts during play. For game designers, the patterns in the data argue for testing longer play sessions and not relying on just one way of adjusting difficulty.

Keywords: dynamic difficulty adjustment, action game design, player experience

DOI: 10.54941/ahfe1007068