Federated Learning for Personalized Game Difficulty Adjustment in Mobile Platforms
Elizabeth Martinez 2025-02-07

Federated Learning for Personalized Game Difficulty Adjustment in Mobile Platforms

Thanks to Elizabeth Martinez for contributing the article "Federated Learning for Personalized Game Difficulty Adjustment in Mobile Platforms".

Federated Learning for Personalized Game Difficulty Adjustment in Mobile Platforms

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.

This paper applies systems thinking to the design and analysis of mobile games, focusing on how game ecosystems evolve and function within the broader network of players, developers, and platforms. The study examines the interdependence of game mechanics, player interactions, and market dynamics in the creation of digital ecosystems within mobile games. By analyzing the emergent properties of these ecosystems, such as in-game economies, social hierarchies, and community-driven content, the paper highlights the role of mobile games in shaping complex digital networks. The research proposes a systems thinking framework for understanding the dynamics of mobile game design and its long-term effects on player behavior, game longevity, and developer innovation.

This study explores the integration of augmented reality (AR) technologies in mobile games, examining how AR enhances user engagement and immersion. It discusses technical challenges, user acceptance, and the future potential of AR in mobile gaming.

This paper explores the integration of artificial intelligence (AI) in mobile game design to enhance player experience through adaptive gameplay systems. The study focuses on how AI-driven algorithms adjust game difficulty, narrative progression, and player interaction based on individual player behavior, preferences, and skill levels. Drawing on theories of personalized learning, machine learning, and human-computer interaction, the research investigates the potential for AI to create more immersive and personalized gaming experiences. The paper also examines the ethical considerations of AI in games, particularly concerning data privacy, algorithmic bias, and the manipulation of player behavior.

This research investigates the ethical and psychological implications of microtransaction systems in mobile games, particularly in free-to-play models. The study examines how microtransactions, which allow players to purchase in-game items, cosmetics, or advantages, influence player behavior, spending habits, and overall satisfaction. Drawing on ethical theory and psychological models of consumer decision-making, the paper explores how microtransactions contribute to the phenomenon of “pay-to-win,” exploitation of vulnerable players, and player frustration. The research also evaluates the psychological impact of loot boxes, virtual currency, and in-app purchases, offering recommendations for ethical monetization practices that prioritize player well-being without compromising developer profitability.

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