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<span class="d-block text-center">Victoria Simmons</span>
<span class="date d-block text-center small text-uppercase text-black-50 mb-5">2025-02-08</span>
<h2 class="heading text-center">Player Typology Modeling Based on Longitudinal Gameplay Data</h2>
<p class="lead mb-4 text-center">Thanks to Victoria Simmons for contributing the article "Player Typology Modeling Based on Longitudinal Gameplay Data".
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<p>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.</p>
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<p>This paper investigates the potential of neurofeedback and biofeedback techniques in mobile games to enhance player performance and overall gaming experience. The research examines how mobile games can integrate real-time brainwave monitoring, heart rate variability, and galvanic skin response to provide players with personalized feedback and guidance to improve focus, relaxation, or emotional regulation. Drawing on neuropsychology and biofeedback research, the study explores the cognitive and emotional benefits of biofeedback-based game mechanics, particularly in improving players' attention, stress management, and learning outcomes. The paper also discusses the ethical concerns related to the use of biofeedback data and the potential risks of manipulating player physiology.</p>
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