AI-Adaptive Difficulty in Games: An Empirical Study

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Authors: Ayush Kumar
Cited by: 0

Abstract

This project presents an empirical study examining whether AI-adaptive difficulty improves player engagement compared to static difficulty in a 2D platformer game. A lightweight, reinforcement-inspired adaptation mechanism dynamically adjusts game parameters based on player performance. Results indicate increased average playtime and reduced retries under adaptive difficulty, suggesting the effectiveness of computationally efficient adaptive game AI systems.

Fields of Study & Subjects

Artificial Intelligence in Games Reinforcement Learning in Robotics Educational Games and Gamification

Publication details

Journal / source
OSF Preprints (OSF Preprints)
Publication date
1 January 2026
Document type
Preprint