Dynamic Content Personalization in Mobile Games Using Contextual Bandits
Carol Campbell 2025-02-04

Dynamic Content Personalization in Mobile Games Using Contextual Bandits

Thanks to Carol Campbell for contributing the article "Dynamic Content Personalization in Mobile Games Using Contextual Bandits".

Dynamic Content Personalization in Mobile Games Using Contextual Bandits

This systematic review examines existing literature on the effects of mobile gaming on mental health, identifying both beneficial and detrimental outcomes. It provides evidence-based recommendations for stakeholders in the gaming industry and healthcare sectors.

This paper examines how mobile games can enhance players’ psychological empowerment by improving their self-efficacy and confidence through gameplay. The research investigates how game mechanics such as challenges, achievements, and skill development contribute to a player's sense of mastery and competence. Drawing on psychological theories of self-efficacy and motivation, the study explores how mobile games can be designed to provide players with a sense of accomplishment and personal growth, particularly in games that focus on skill-based tasks, puzzles, and strategy. The paper also explores the impact of mobile games on players' overall well-being, particularly in terms of their confidence and ability to overcome challenges in real life.

This paper explores the application of artificial intelligence (AI) and machine learning algorithms in predicting player behavior and personalizing mobile game experiences. The research investigates how AI techniques such as collaborative filtering, reinforcement learning, and predictive analytics can be used to adapt game difficulty, narrative progression, and in-game rewards based on individual player preferences and past behavior. By drawing on concepts from behavioral science and AI, the study evaluates the effectiveness of AI-powered personalization in enhancing player engagement, retention, and monetization. The paper also considers the ethical challenges of AI-driven personalization, including the potential for manipulation and algorithmic bias.

A Comparative Analysis This paper provides a comprehensive analysis of various monetization models in mobile gaming, including in-app purchases, advertisements, and subscription services. It compares the effectiveness and ethical considerations of each model, offering recommendations for developers and policymakers.

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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