Emily Carter
2025-02-01
Adaptive Pathfinding Algorithms for Procedurally Generated Mobile Game Levels
Thanks to Emily Carter for contributing the article "Adaptive Pathfinding Algorithms for Procedurally Generated Mobile Game Levels".
This study leverages mobile game analytics and predictive modeling techniques to explore how player behavior data can be used to enhance monetization strategies and retention rates. The research employs machine learning algorithms to analyze patterns in player interactions, purchase behaviors, and in-game progression, with the goal of forecasting player lifetime value and identifying factors contributing to player churn. The paper offers insights into how game developers can optimize their revenue models through targeted in-game offers, personalized content, and adaptive difficulty settings, while also discussing the ethical implications of data collection and algorithmic decision-making in the gaming industry.
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