Hierarchical Reinforcement Learning for Complex Task Decomposition in Mobile Games
Brandon Barnes 2025-02-07

Hierarchical Reinforcement Learning for Complex Task Decomposition in Mobile Games

Thanks to Brandon Barnes for contributing the article "Hierarchical Reinforcement Learning for Complex Task Decomposition in Mobile Games".

Hierarchical Reinforcement Learning for Complex Task Decomposition in Mobile Games

This paper explores the use of mobile games as educational tools, assessing their effectiveness in teaching various subjects and skills. It discusses the advantages and limitations of game-based learning in mobile contexts.

From the nostalgic allure of retro classics to the cutting-edge simulations of modern gaming, the evolution of this immersive medium mirrors humanity's insatiable thirst for innovation, escapism, and boundless exploration. The rich tapestry of gaming history is woven with iconic titles that have left an indelible mark on pop culture and inspired generations of players. As technology advances and artistic vision continues to push the boundaries of what's possible, the gaming landscape evolves, offering new experiences, genres, and innovations that captivate and enthrall players worldwide.

This paper investigates the role of social influence in mobile games, focusing on how social networks, peer pressure, and social comparison affect player behavior and in-game purchasing decisions. The study examines how features such as leaderboards, friend lists, and social sharing options influence players’ motivations to engage with the game and spend money on in-game items. Drawing on social psychology and behavioral economics, the research explores how players' decisions are shaped by their interactions with others in the game environment. The paper also discusses the ethical implications of using social influence to drive in-game purchases, particularly in relation to vulnerable players and addiction risk.

This paper explores the integration of artificial intelligence (AI) in mobile game design to enhance player experience through adaptive gameplay systems. The study focuses on how AI-driven algorithms adjust game difficulty, narrative progression, and player interaction based on individual player behavior, preferences, and skill levels. Drawing on theories of personalized learning, machine learning, and human-computer interaction, the research investigates the potential for AI to create more immersive and personalized gaming experiences. The paper also examines the ethical considerations of AI in games, particularly concerning data privacy, algorithmic bias, and the manipulation of player behavior.

This study examines the impact of cognitive load on player performance and enjoyment in mobile games, particularly those with complex gameplay mechanics. The research investigates how different levels of complexity, such as multitasking, resource management, and strategic decision-making, influence players' cognitive processes and emotional responses. Drawing on cognitive load theory and flow theory, the paper explores how game designers can optimize the balance between challenge and skill to enhance player engagement and enjoyment. The study also evaluates how players' cognitive load varies with game genre, such as puzzle games, action games, and role-playing games, providing recommendations for designing games that promote optimal cognitive engagement.

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