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Lecturer
Georgios N. Yannakakis, georgios.yannakakakis@um.edu.mt
Content and organization
The primary goal of the course is to revisit the field of game artificial intelligence (AI) and introduce non-traditional uses of AI in games. A short introduction will be given on AI areas that are currently reshaping the game AI research and development roadmap including procedural content generation, player experience modeling, and AI-based game design. The primary focus of the course, however, will be on player modeling (spanning from game analytics and game data mining to affective computing methods). Within game data mining, emphasis will be given to state-of-the-art data analytics/mining algorithms and methods for improving the gameplay experience and game development procedures. Within affective computing, emphasis will be given in the phases of emotion elicitation, emotion recognition (feature extraction, feature selection, annotation, classification, regression, preference learning), emotion expression (e.g., facial expression, agent behavioural responses, etc.) and affect-driven adaptation (interaction elements adapt to the user needs/affect).
Level
Graduate
Course Duration
3 hours per week
Course Type
Semester Course
Participation terms
Please email the lecturer for further details on how to join the course.
Lecture Plan
https://sites.google.com/view/mscindigitalgames/courses/player-modeling-idg5159#h.sb9dgesqnccp
Language
English
Modality (online/in person):
Online lectures + in person tutorials
