Joyce Stevens
2025-02-08
Self-Learning Algorithms for Autonomous World Evolution in Games
Thanks to Joyce Stevens for contributing the article "Self-Learning Algorithms for Autonomous World Evolution in Games".
This research examines the role of geolocation-based augmented reality (AR) games in transforming how urban spaces are perceived and interacted with by players. The study investigates how AR mobile games such as Pokémon Go integrate physical locations into gameplay, creating a hybrid digital-physical experience. The paper explores the implications of geolocation-based games for urban planning, public space use, and social interaction, considering both the positive and negative effects of blending virtual experiences with real-world environments. It also addresses ethical concerns regarding data privacy, surveillance, and the potential for gamifying everyday spaces in ways that affect public life.
This paper explores the potential of mobile games to serve as therapeutic tools in the treatment of mental health conditions, such as anxiety, depression, and PTSD. It examines how game mechanics and immersive environments can be used to provide psychological relief, improve emotional regulation, and facilitate cognitive-behavioral therapy. The study discusses challenges in integrating therapeutic design with traditional game elements and offers recommendations for the development of clinically effective mobile health games.
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 research investigates how machine learning (ML) algorithms are used in mobile games to predict player behavior and improve game design. The study examines how game developers utilize data from players’ actions, preferences, and progress to create more personalized and engaging experiences. Drawing on predictive analytics and reinforcement learning, the paper explores how AI can optimize game content, such as dynamically adjusting difficulty levels, rewards, and narratives based on player interactions. The research also evaluates the ethical considerations surrounding data collection, privacy concerns, and algorithmic fairness in the context of player behavior prediction, offering recommendations for responsible use of AI in mobile games.
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.
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