Doris Patterson
2025-02-07
Multi-Objective Reinforcement Learning for Player-Centric AI Design
Thanks to Doris Patterson for contributing the article "Multi-Objective Reinforcement Learning for Player-Centric AI Design".
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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