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< Back Simultaneous multi-view object recognition and grasping in open-ended domains Link Author(s) H Kasaei, S Luo, R Sasso, M Kasaei 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. Player Research Limited

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. IGDA

< Back Why Choose You?-Exploring Attitudes Towards Starter Pokémon Link Author(s) T Best, YJ Hsu Abstract More info TBA Link

< Back 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? Project areas include: AI agents that play games using Deep Reinforcement Learning and Statistical forward planning AI agents as non-player characters General Video Game AI - AI that can be transferred between video games AI agents for game balancing and Quality Assurance testing << Previous Theme page Next Theme page >> iGGi >>> People <<< relevant to this Theme: Michael Aichmüller iGGi Alum Game AI, Applied Games Read More Dr Martin Balla iGGi Alum Game AI Read More Dr Daniel Berio iGGi Alum Game AI Read More Dr Ignacio Castro Supervisor Game AI, Applied Games, Player Research, Game Data Read More Dr Memo Akten iGGi Alum Game AI Read More Prof. Richard Bartle Supervisor Design & Development, Game AI, Player Research Read More Toby Best iGGi PG Researcher Available for placement Game AI, Design & Development, Player Research Read More Dr Tom Cole iGGi Alum + Supervisor Game AI, Design & Development Read More Dr Myat Aung iGGi Alum Game AI Read More Matt Bedder iGGi Alum Game AI Read More Dr Ivan Bravi iGGi Alum Game AI, Player Research Read More Dr Tom Collins Supervisor Game AI, Game Audio, Game Data, Player Research, Esports Read More Load More iGGi People working in this Theme iGGi >>> Publications <<< relevant to this Theme: Tiny Moves: Game-based Hypothesis Refinement A Dobrowolska, R Hintzen, M Balla, K Gemayel, S Reichert, T Charman, ... arXiv preprint arXiv:2602.09801, 2026 Dr Martin Balla View Details Gaze for Dyads & Blinks for Triads: Task Engagement Predictors in Free-Flow VR Interactions C Gonzalez Diaz, GC Dobre, E Andre, C Conati 2026 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR) Dr Cristina Dobre View Details Beyond the Spotlight: Co-Designing AI for Theatre Audience Communication A Pedrassoli Chitayat, S Carter, BA Robertson, J Hook Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems Dr Alan Pedrassoli Chitayat View Details Language Model Inversion through End-to-End Differentiation KY Denamganaï, K Subr arXiv preprint arXiv:2602.11044, 2026 Dr Kevin Denamganaï View Details Statistical Forward Planning Algorithms SM Lucas, J Goodman, M Tot Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2025 Dr Marko Tot View Details World and human action models towards gameplay ideation A Kanervisto, D Bignell, LY Wen, M Grayson, R Georgescu, ... Nature 638 (8051), 656-663, 2025 Dr Marko Tot View Details Load More iGGi Publications for this Theme Previous Next

< Back Towards Friendly Mixed Initiative Procedural Content Generation: Three Pillars of Industry Link Author(s) G Lai, W Latham, FF Leymarie Abstract More info TBA Link

< Back Behavioural Cloning in VizDoom Link Author(s) R Spick, T Bradley, A Raina, PV Amadori, G Moss 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:

< Back Self-determination theory in HCI: advancing the field Link Author(s) Nick Ballou, Dorian Peters, Gabriela Villalobos-Zúñiga, Elisa D Mekler, Rafael A Calvo, Sebastian Deterding Abstract More info TBA Link

< Back Reforms to improve reproducibility and quality must be coordinated across the research ecosystem: the view from the UKRN Local Network Leads Link Author(s) SLK Stewart, CR Pennington, GR da Silva, N Ballou, J Butler, Z Dienes, ... 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. Creative Assembly

< Back Synthesising Knocking Sound Effects Using Conditional WaveGAN Link Author(s) A Barahona-Rıos, S Pauletto Abstract More info TBA Link