Energy-Efficient AI Architectures for Computationally Intensive Mobile Games
Barbara Garcia 2025-02-07

Energy-Efficient AI Architectures for Computationally Intensive Mobile Games

Thanks to Barbara Garcia for contributing the article "Energy-Efficient AI Architectures for Computationally Intensive Mobile Games".

Energy-Efficient AI Architectures for Computationally Intensive Mobile Games

This study applies social network analysis (SNA) to investigate the role of social influence and network dynamics in mobile gaming communities. It examines how social relationships, information flow, and peer-to-peer interactions within these communities shape player behavior, preferences, and engagement patterns. The research builds upon social learning theory and network theory to model the spread of gaming behaviors, including game adoption, in-game purchases, and the sharing of strategies and achievements. The study also explores how mobile games leverage social influence mechanisms, such as multiplayer collaboration and social rewards, to enhance player retention and lifetime value.

This research examines the application of Cognitive Load Theory (CLT) in mobile game design, particularly in optimizing the balance between game complexity and player capacity for information processing. The study investigates how mobile game developers can use CLT principles to design games that maximize player learning and engagement by minimizing cognitive overload. Drawing on cognitive psychology and game design theory, the paper explores how different types of cognitive load—intrinsic, extraneous, and germane—affect player performance, frustration, and enjoyment. The research also proposes strategies for using game mechanics, tutorials, and difficulty progression to ensure an optimal balance of cognitive load throughout the gameplay experience.

This paper explores the role of artificial intelligence (AI) in personalizing in-game experiences in mobile games, particularly through adaptive gameplay systems that adjust to player preferences, skill levels, and behaviors. The research investigates how AI-driven systems can monitor player actions in real-time, analyze patterns, and dynamically modify game elements, such as difficulty, story progression, and rewards, to maintain player engagement. Drawing on concepts from machine learning, reinforcement learning, and user experience design, the study evaluates the effectiveness of AI in creating personalized gameplay that enhances user satisfaction, retention, and long-term commitment to games. The paper also addresses the challenges of ensuring fairness and avoiding algorithmic bias in AI-based game design.

This research explores the evolution of game monetization models in mobile games, with a focus on player preferences and developer strategies over time. By examining historical data and trends from the mobile gaming industry, the study identifies key shifts in monetization practices, such as the transition from premium models to free-to-play with in-app purchases (IAP), subscription services, and ad-based monetization. The research also investigates how these shifts have impacted player behavior, including spending habits, game retention, and perceptions of value. Drawing on theories of consumer behavior, the paper discusses the relationship between monetization models and player satisfaction, providing insights into how developers can balance profitability with user experience while maintaining ethical standards.

This research evaluates the environmental sustainability of the mobile gaming industry, focusing on the environmental footprint of game development, distribution, and consumption. The study examines energy consumption patterns, electronic waste generation, and resource use across the mobile gaming lifecycle, offering a comprehensive assessment of the industry's impact on global sustainability. It also explores innovative approaches to mitigate these effects, such as green game design principles, eco-friendly server technologies, and sustainable mobile device manufacturing practices.

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