Starts on

Ends on

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).

Course Type

ai-phd Course

Host Institution
Institute of Digital Games, University of Malta

Other short courses

11. 05. 2022 Go

Geometric learning

05. 04. 2022 Go

Computer Graphics

04. 04. 2022 Go

Bayesian Learning

02. 04. 2022 Go

Computer Graphics

31. 03. 2022 Go

Web of Data

27. 03. 2022 Go

Machine Learning

02. 03. 2022 Go

Player Modeling

28. 02. 2022 Go

Player Modeling

21. 02. 2022 Go

Affective Computing

21. 02. 2022 Go

Machine Listening

21. 02. 2022 Go

Computer Vision

21. 02. 2022 Go

Computer Vision

21. 02. 2022 Go

Self-Driving Cars

21. 02. 2022 Go