AI Algorithms in Gamification
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 112
Special Issue Editors
Interests: gamification; virtual reality; augmented reality; mixed reality; human information processing; computer game design and development; simulation system design and engineering; human computer interaction
Special Issues, Collections and Topics in MDPI journals
Interests: sensor fusion; embedded systems; machine learning; computer vision; propagation modelling; IoT; urban data science
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Special Issue Information
Dear Colleagues,
In this Special Issue, due to the rise of Artificial Intelligence (AI) in gamification, we will focus on how to incorporate AI technologies into gamification to enhance user engagement and motivation. Gamification is the use of game mechanics and design principles in non-game contexts to motivate and engage people. It has been widely adopted in various fields, including education, marketing, and employee engagement. There are many advantages of AI in gamification, including the following:
Personalisation: AI can add a level of personalization to gamification with the use of Machine Learning algorithms to analyze user data. Using Data Analytics, developers can create tailored experiences customized to individual players. This can lead to a more engaging and immersive experience better suited to each individual's preferences and interests. Using AI in gamification and its ability to learn from user data, developers can create a personalized experience that adapts to user's needs by analyzing user behavior and preferences. This can include recommendations for content or activities, personalized challenges or rewards, and even predictive analytics that anticipate what the user might want or need next.
Socialization: AI can also enhance the social aspect of gamification by analyzing user data to create more meaningful interactions between players. By analyzing social connections and user behavior, AI can create personalized recommendations for social interactions based on shared interests or skill levels. This can lead to a more collaborative and supportive gaming experience that fosters a sense of community.
Communication: A gamified learning platform using Natural Language Processing (NLP) and Large Language Models (LLMs) to analyze and understand human language and user responses can provide personalized feedback tailored to each individual's strengths and weaknesses. This could lead to a more engaging and effective learning experience better suited to each user's needs.
Adaptation: AI can also be used to create more dynamic and adaptive gamification experiences. Using Machine Learning to analyze user data, gamification designers can create experiences that adapt and evolve over time, including personalized challenges with adjusted difficulty levels as the user progresses as well as dynamic rewards that change based on user behavior.
Prof. Dr. Manolya Kavakli-Thorne
Dr. Zhuangzhuang Dai
Dr. Seif Allah El Mesloul Nasri
Guest Editors
Manuscript Submission Information
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Keywords
- machine Learning
- AI-driven gamification
- game theory
- game-based learning
- user experience
- virtual environments
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