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<img src="https://x.mit-edu.top/static/images/user/10.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">Emma Price</span>
<span class="date d-block text-center small text-uppercase text-black-50 mb-5">2025-01-31</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 Emma Price for contributing the article "Optimizing Deep Reinforcement Learning Models for Procedural Content Generation in Mobile Games".
</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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