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< Back Design and implementation of TAG: a tabletop games framework Link ​ Author(s) RD Gaina, M Balla, A Dockhorn, R Montoliu, D Perez-Liebana Abstract ​ More info TBA ​ Link

< Back How Players Learn Team-versus-Team Esports: First Results from A Grounded Theory Study Link ​ Author(s) J Hesketh, CS Deterding, J Gow Abstract ​ More info TBA ​ Link

< Back IoT and Machine Learning for Next Generation Traffic Systems Link ​ Author(s) S Howell, S Cole, T Broad, T Maatta Abstract ​ More info TBA ​ Link

< Back The Effects of a Soundtrack on Board Game Player Experience Link ​ Author(s) T Farkas, A Denisova, S Wiseman, R Fiebrink Abstract ​ More info TBA ​ Link

< Back DAX: Data-Driven Audience Experiences in Esports Link ​ Author(s) A Kokkinakis, SP Demediuk, I Nölle, O Olarewaju, S Patra, J Robertson, P York, AP Chitayat, A Coates, D Slawson, P Hughes, N Hardie, B Kirman, JD Hook, A Drachen, M Ursu, FO Block Abstract ​ More info TBA ​ Link

< Back Network Bending: Expressive Manipulation of Generative Models in Multiple Domains Link ​ Author(s) T Broad, FF Leymarie, M Grierson Abstract ​ More info TBA ​ Link

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. Revolution

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. Yokozuna Data

< Back Practical Game Design Tool: State Explorer Link ​ Author(s) R Volkovas, M Fairbank, JR Woodward, S Lucas Abstract ​ More info TBA ​ Link

< Back ReferentialGym: A Nomenclature and Framework for Language Emergence & Grounding in (Visual) Referential Games Link ​ Author(s) K Denamganaï, JA Walker Abstract ​ More info TBA ​ Link

Evolving Perception for Game Agents Theme Game AI Project proposed & supervised by Alex Wade, Peter Cowling To discuss whether this project could become your PhD proposal please email: alex.wade@york.ac.uk < Back ​ Evolving Perception for Game Agents Project proposal abstract: How does perception emerge? Hugely successful approaches to creating AI game playing agents such as MuZero, AlphaGo and AlphaStar learn the action to take in each state alongside a representation of the world to aid learning. For MuZero, AlphaGo and AlphaStar the representation is a prior distribution on how promising each move is in a given board position. The prior distribution can be seen as a highly effective way to perceive and simplify the game world, for greater decision-making fitness. In this project we will create game agents, for open world games such as Minecraft, which start from rudimentary sensors and simultaneously evolve a world representation while learning to make decisions leading to high fitness in the game world. We will investigate important scientific questions about how perception has evolved in humans, alongside creating interesting agents which might exhibit very weird and "alien" behaviours. Our internal representation of the world is conditioned both by evolution (for example, the physiology of the eye and brain) and also by learned experience. What sorts of perceptual systems might artificial agents develop in a simulated world? In this project we will develop simple 'open world' games into which we will release software agents with rudimentary sensory systems, possibly alongside human-controlled agents. These agents will be able to sense their world but not, initially, to perceive it (since perception is a combination of sensing and interpretation ). Both the sensory apparatus and the structure of the machine learning networks will be free to evolve (through genetic algorithms and reinforcement learning). Each generation will need to undergo a period of 'development' to train its networks on the current environment. We seek a motivated and talented student with a creative approach to research and skills in some of AI/machine learning, programming/game design, psychology/neuroscience and data analysis, and a willingness to learn new skills as necessary. Some travel to other international labs with an interest in this space may be possible. Supervisor: Alex Wade , Peter Cowling Based at:

iGGi PhD Projects 2023 Game Data This page displays the supervisor-proposed PhD projects on offer under the above stated theme: If you are interested in any of the projects listed and would like further details and/or to discuss, please email the project supervisor. Please note that you can also frame your own project independently granted that you have secured a supervisor's support. For a list of available supervisors please see the accepting students section of our website. ​ While iGGi has checked that the project descriptions listed below are within iGGi's scope , we wish to highlight that you are still responsible for ensuring that your proposal, too, is in line with this scope, and we would further like to point out that supervisor-framed projects are not prioritised in the application selection process: they are judged by the same criteria as applicant-framed proposals. For guidance to make sure that the proposal you submit (regardless of whether it has been supervisor-framed or created entirely by you) sits within iGGi's scope please refer to this link: https://iggi.org.uk/iggi-scope Navigate to other Themes on offer: Game AI Design & Development Player Research Game Audio Game Data Immersive Technology Creative Computing E-Sports Applied Games Back to ALL Projects Game Data ​ Building Player Profiles in Mobile Monetisation: A Machine Learning Approach This project aims to use machine learning techniques to segment and profile mobile gamers in terms of their in-game spending. Price Game Data Duration David Zendle Read More Game Data ​ Understanding ongoing mental states using video games: applications to mental health research. This project will use a combination of neuroscience and advanced data analysis methods to examine the link between video game play and the brain. We will use a combination of cutting-edge data analytic techniques applied to large, existing video game telemetry datasets and neuroimaging experiments designed to measure changes in ongoing mental states while people play simple video games. Price Game Data Duration Alex Wade Read More Load More