Player-Centric Game Balancing Through Reinforcement Learning and Multi-Agent Systems
Donald Green 2025-02-01

Player-Centric Game Balancing Through Reinforcement Learning and Multi-Agent Systems

Thanks to Donald Green for contributing the article "Player-Centric Game Balancing Through Reinforcement Learning and Multi-Agent Systems".

Player-Centric Game Balancing Through Reinforcement Learning and Multi-Agent Systems

This research explores the relationship between mobile gaming habits and academic performance among students. It examines both positive aspects, such as improved cognitive skills, and negative aspects, such as decreased study time and attention.

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 research investigates the use of mobile games in health interventions, particularly in promoting positive health behavior changes such as physical activity, nutrition, and mental well-being. The study examines how gamification elements such as progress tracking, rewards, and challenges can be integrated into mobile health apps to increase user motivation and adherence to healthy behaviors. Drawing on behavioral psychology and health promotion theories, the paper explores the effectiveness of mobile games in influencing health-related outcomes and discusses the potential for using game mechanics to target specific health issues, such as obesity, stress management, and smoking cessation. The research also considers the ethical implications of using gaming techniques in health interventions, focusing on privacy concerns, user consent, and data security.

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 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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