Is artificial Intelligence (AI) currently of any help for the design and development of games? Can game agents and non-player characters get any smarter or are there better (and smarter) uses of AI within games? Can we instead use AI to automatically design new games? Or, alternatively, use AI to understand how players feel, think and react? What can we learn after mining massive sets of player data about the games we design and how can this information help us design even better games? In this talk, I address the above questions by presenting three key game AI areas that are currently reshaping research and development in the field. These game AI areas include the computational modeling of player experience, the procedural generation of game content and the mining of big (player behavioral) data. I will also discuss opportunities for studying games (their design and technology) at the Institute of Digital Games, University of Malta.
Bio of speaker
Georgios N. Yannakakis is Associate Professor at the Institute of Digital Games, University of Malta (UoM). He received the Ph.D. degree in Informatics from the University of Edinburgh in 2005. Prior to joining the Institute of Digital Games, UoM, in 2012 he was an Associate Professor at the Center for Computer Games Research at the IT University of Copenhagen.
He does research at the crossroads of AI (computational intelligence, preference learning, computational creativity), affective computing (emotion detection, emotion annotation), advanced game technology (player experience modeling, procedural content generation, personalization) and human-computer interaction (multimodal interaction, psychophysiology, user modeling). He pursues research concepts such as user experience modeling and procedural content generation for the design of personalized interactive systems for entertainment, education, training and health. Georgios N. Yannakakis is one of the leading researchers within player affective modeling and adaptive content generation for games. He has pioneered the use of preference learning algorithms to create statistical models of player experience which drive the automatic generation of personalized game content. He has published over 150 journal and conference papers in the aforementioned fields and his work has been cited broadly. His research has been supported by numerous national and European grants.
He is an Associate Editor of the IEEE Transactions on Affective Computing and the IEEE Transactions on Computational Intelligence and AI in Games. He has been the General Chair of key conferences in the area of game artificial intelligence (IEEE CIG 2010) and games research (FDG 2013).