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<img src="https://x.mit-edu.top/static/images/user/3.jpg" alt="Deep Reinforcement Learning for Adaptive Difficulty Adjustment in Games" title="Deep Reinforcement Learning for Adaptive Difficulty Adjustment in Games" class="author-pic img-fluid rounded-circle mx-auto">
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<span class="d-block text-center">Alice Coleman</span>
<span class="date d-block text-center small text-uppercase text-black-50 mb-5">2025-02-04</span>
<h2 class="heading text-center">Deep Reinforcement Learning for Adaptive Difficulty Adjustment in Games</h2>
<p class="lead mb-4 text-center">Thanks to Alice Coleman for contributing the article "Deep Reinforcement Learning for Adaptive Difficulty Adjustment in Games".
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<p>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.</p>
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