< Back The impact of stiffness in bimanual versus dyadic interactions requiring force exchange Link Author(s) N Pena-Perez, SA Mutalib, J Eden, I Farkhatdinov, E Burdet Abstract More info TBA Link

< Back Evaluating Generalization in General Video Game Playing Link Author(s) D Perez-Liebana, M Balla, S Lucas Abstract More info TBA Link

< Back “Clinically significant distress” in Internet Gaming Disorder: An individual participant meta-analysis Link Author(s) N Ballou, D Zendle Abstract More info TBA Link

Novelty Optimisation Theme Creative Computing Project proposed & supervised by Jeremy Gow, Sebastian Deterding To discuss whether this project could become your PhD proposal please email: jeremy.gow@qmul.ac.uk < Back Novelty Optimisation Project proposal abstract: New levels, new characters, new items, new opponents: Novelty is a major game feature stoking sustained player curiosity and interest. Too much repetition, and players get bored. But is there such a thing as too much novelty? Games already do automatic difficulty balancing – finding just the right level of challenge. Can we do the same for novelty – identify and automatically balance the right amount of novel content we serve to players? This project would benefit from a computational methods background, such as computational psychology, cognitive science, machine learning, or procedural content generation, and an interest in player psychology. Supervisor: Jeremy Gow , Sebastian Deterding Based at:

Principled and Scalable Exploration Techniques for Reinforcement Learning Theme Game AI Project proposed & supervised by Paulo Rauber To discuss whether this project could become your PhD proposal please email: p.rauber@qmul.ac.uk < Back Principled and Scalable Exploration Techniques for Reinforcement Learning Project proposal abstract: Reinforcement learning has received significant attention due to its success in training agents that play popular games such as Go , Starcraft II , Dota 2 , and others. Inefficient exploration, one of the earliest problems recognized in the field, still limits the success of reinforcement learning approaches that do not require domain knowledge. Although techniques like posterior sampling convincingly solve hard exploration problems in simple domains ( https://searchworks.stanford.edu/view/11891201 ), scalable exploration techniques remain elusive. In this project, you will develop principled and scalable exploration techniques based on reducing model uncertainty ( https://arxiv.org/abs/1609.04436 ). Besides benefiting from games as excellent testbeds, this project has the potential to radically improve automated playtesting. Supervisor: Paulo Rauber Based at:

iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Knowledge Transfer Network

< Back Program Committee and Subreviewers Link Author(s) M Balla, I Bravi, H Abbass, M Aitchison, M Aittala, D Anderson, D Ashlock, S Azad, ... Abstract More info TBA Link

< Back Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access Link Author(s) RJ Spick, JA Walker Abstract More info TBA Link

< Back Investigating sensorimotor contingencies in the enactive interface Link Author(s) JK Gibbs, K Devlin Abstract More info TBA Link

< Back Testing game mechanics in games with a purpose for NLP applications Link Author(s) C Madge, J Chamberlain, R Bartle, U Kruschwitz, M Poesio Abstract More info TBA Link

< Back Perceived value of video games, but not hours played, predicts mental well-being in adult Nintendo players Link Author(s) N Ballou, M Vuorre, T Hakman, K Magnusson, AK Przybylski Abstract More info TBA Link

Themes (All) iGGi is a collaboration between Uni of York + Queen Mary Uni of London: the largest training programme worldwide for doing a PhD in digital games. iGGi Themes Game AI How might we use novel AI techniques including machine learning and decision search to create more effective and engaging game agents and understand human behaviour in games? Design & Development How might we advance game-making with new design and development insights, methods, tools, and techniques? Immersive Technology How might we advance the use and understanding of VR, XR, AR, and other immersive technologies in games? Game Audio How might we combine data, AI, and music psychology to create engaging adaptive music and sound experiences for games? Esports How might we use esports data to create immersive audience experiences, help players and teams improve, and understand human performance? Applied Games How might we design and use games to support health, learning, work, and conduct scientific research? Creative Computing How can AI tools enhance the creative process of (human) game creatives? Player Research How might we use and combine diverse methods to understand how people experience games, interact with and through them, and are affected by them? Accessibility How might we design and make games playable and inclusive to as wide a range of people as possible, regardless of background or ability? Game Data How might we analyse the big data exhausts of games to support game developers and understand people inside and outside of games?