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<img src="https://x.mit-edu.top/static/images/user/9.jpg" alt="Optimizing Deep Reinforcement Learning Models for Procedural Content Generation in Mobile Games" title="Optimizing Deep Reinforcement Learning Models for Procedural Content Generation in Mobile Games" class="author-pic img-fluid rounded-circle mx-auto">
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<span class="d-block text-center">Jerry Fisher</span>
<span class="date d-block text-center small text-uppercase text-black-50 mb-5">2025-02-03</span>
<h2 class="heading text-center">Optimizing Deep Reinforcement Learning Models for Procedural Content Generation in Mobile Games</h2>
<p class="lead mb-4 text-center">Thanks to Jerry Fisher for contributing the article "Optimizing Deep Reinforcement Learning Models for Procedural Content Generation in Mobile Games".
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<p>This study presents a multidimensional framework for understanding the diverse motivations that drive player engagement across different mobile game genres. By drawing on Self-Determination Theory (SDT), the research examines how intrinsic and extrinsic motivation factors—such as achievement, autonomy, social interaction, and competition—affect player behavior and satisfaction. The paper explores how various game genres (e.g., casual, role-playing, and strategy games) tailor their game mechanics to cater to different motivational drivers. It also evaluates how player motivation impacts retention, in-game purchases, and long-term player loyalty, offering a deeper understanding of game design principles and their role in shaping player experiences.</p>
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<p>This research investigates the environmental footprint of mobile gaming, including energy consumption, electronic waste, and resource usage. It proposes sustainable practices for game development and consumption.This study examines how mobile gaming serves as a platform for social interaction, allowing players to form and maintain relationships. It explores the dynamics of online communities and the social benefits of gaming.</p>
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