Spatiotemporal Challenges in AR Game Design: A Computational Perspective
Karen Harris 2025-02-06

Spatiotemporal Challenges in AR Game Design: A Computational Perspective

Thanks to Karen Harris for contributing the article "Spatiotemporal Challenges in AR Game Design: A Computational Perspective".

Spatiotemporal Challenges in AR Game Design: A Computational Perspective

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.

This paper explores how mobile games can be used to raise awareness about environmental issues and promote sustainable behaviors. Drawing on environmental psychology and game-based learning, the study investigates how game mechanics such as resource management, ecological simulations, and narrative-driven environmental challenges can educate players about sustainability. The research examines case studies of games that integrate environmental themes, analyzing their impact on players' attitudes toward climate change, waste reduction, and conservation efforts. The paper proposes a framework for designing mobile games that not only entertain but also foster environmental stewardship and collective action.

This research investigates the cognitive benefits of mobile games, focusing on how different types of games can enhance players’ problem-solving abilities, decision-making skills, and critical thinking. The study draws on cognitive psychology, educational theory, and game-based learning research to examine how game mechanics, such as puzzles, strategy, and role-playing, promote higher-order thinking. The paper evaluates the potential for mobile games to be used as tools for educational development and cognitive training, particularly for children, students, and individuals with cognitive impairments. It also considers the limitations of mobile games in fostering cognitive development and the need for a balanced approach to game design.

This study examines the sustainability of in-game economies in mobile games, focusing on virtual currencies, trade systems, and item marketplaces. The research explores how virtual economies are structured and how players interact with them, analyzing the balance between supply and demand, currency inflation, and the regulation of in-game resources. Drawing on economic theories of market dynamics and behavioral economics, the paper investigates how in-game economic systems influence player spending, engagement, and decision-making. The study also evaluates the role of developers in maintaining a stable virtual economy and mitigating issues such as inflation, pay-to-win mechanics, and market manipulation. The research provides recommendations for developers to create more sustainable and player-friendly in-game economies.

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.

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