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< Back Learning dynamic graffiti strokes with a compliant robot Link Author(s) D Berio, S Calinon, FF Leymarie Abstract More info TBA Link

< Back Using Virtual Reality to Investigate the Influence of Sleep Deprivation on In-the-Moment Arousal During Exposure to Prolonged Threats Link Author(s) E Sullivan, C McCall, LM Henderson, M Croissant, G Schofield, S Cairney Abstract More info TBA Link

A Word from The iGGi Director 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. A Word from the Director Welcome to iGGi! Below are a few words about the vision for iGGi, about who funds iGGi and why, and about why i GGi can be a force for good in a sometimes turbulent world. iGGi is short for the “EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence” (EPSRC is short for “Engineering and Physical Sciences Research Council”). You can see why the name iGGi stuck! In , 120 PhD students spend 4 years learning cool stuff and conducting research in topics related to games and the games industry, working with 100 UK games companies . The big vision for iGGi is to inject research innovations and innovative researchers into the games industry. There is a strong economic argument for this, and there are even stronger social and cultural reasons. So where did iGGi come from and what is the vision that allowed us to win £30 million for games research? In the early 2000s, the games research community went through a huge growth spurt (which continues to this day). The economic, social and cultural power of video games meant that politicians and funders could no longer brush games aside as kid’s stuff. An opportunity arose in 2013 with the announcement of a competition for funding around 100 centres for PhD research in a focussed area of science or engineering. While it was clear that the call would be massively oversubscribed and very competitive, games seemed a good fit given the rise and rise of the financial size of the games market and the growing research community. We had more and more friends and contacts in the games industry. And we had shown that games could be funded at scale via projects such as UCT (£1.5 million) and NEMOG (1.2 million). A group of people from across academia and industry, with an interest in games research, came together to submit a bid and form a consortium. Our joint goal was to “make better games” and “make games better”. My role in this (as ‘Principal Investigator’) was as a synthesiser of ideas, as a recruiter of people who shared and refined these ideas, and as a writer and lobbyist who could package them up for referees who almost certainly lacked enthusiasm for games research. So how can we summarise the iGGi vision? The ‘IG’ in iGGi stands for ‘Intelligent Games’ - using research advances to make better games that provide richer, more fun experiences. The ‘GI’ in iGGi stands for ‘Game Intelligence’ - research which uses games to understand and inform people. In more detail: the following two paragraphs, from the 2013 iGGi bid, were probably among the most carefully written of the text in the whole bid document (redrafted dozens of times): Our vision is twofold: Intelligent Games: iGGi PhDs, investigators and collaborators will use research advances to seed the creation of a new generation of more intelligent and engaging digital games, to underpin the distinctiveness and growth of the UK games industry. We will weave technical and creative disciplines: using games as an application area to advance research in areas including artificial intelligence and computational creativity; human-computer interaction; interactive sound, graphics and narrative; robotics, agents and complex systems. The study of intelligent games will be underpinned by new business models and by research advances in data mining (game analytics) which can exploit vast volumes of gameplay data. Game Intelligence: iGGi PhDs, investigators and collaborators will investigate games as a medium to achieve scientific and societal goals, working with user groups and the games industry to produce new genres of games which can yield therapeutic, educational and social benefits and using games to seed a new era of scientific experimentation into human preference and interaction. We will create new games to conduct large-scale analysis of individual behaviour, leading to better understanding in economics, psychology, sociology, biology and human-computer interaction. We will build games which promote physical and mental health and educational achievement, underpinned by advances in mobile technology and data mining. This vision was refined and updated for the 2018 iGGi resubmission, especially given the enormous advances in machine learning and the cultural and social successes of games, but the text above remains a good overview of the high-level iGGi vision. But a vision is relatively static, and now, of course, iGGi is a community of brilliant, fun, caring, intelligent, curious research students, supported by staff and industry partners. So maybe the best way to find out more about iGGi is to read more about a few of them… I look forward to talking about games research with you! Peter Cowling iGGi Director Professor of AI, Queen Mary University of London

iGGi PhD Projects - listing iGGi PhD Projects 2023 Player Research 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 Player Research Modelling the interactions in metaverse videogames This project will seek to inform AR and VR enabled videogames by analysing existing online platforms supporting these technologies. Price Player Research Duration Ignacio Castro Read More Load More

< Back iGGi Research Retreat "Unconference" Group Outcomes The Future of AI The "Problem" We discussed what the "future of AI" might look like, how it will change us as a society (for better and worse) and what possibilities it would create in the future. What we did As you can imagine, the "future of AI" is somewhat of a broad and undirected topic. Therefore in the morning we allowed free flowing conversations to see where it went and then towards the end tried to join up the threads into the things that we thought were the most worthy of further analysis and thought. In the afternoon we tackled the specifics of how to approach a game with emergent characters and stories, a topic oft dreamed of by game designers, but hitherto unattainable. The "Outcome" The morning discussions: Our discussions were wide-ranging, but the opening question captured the essence of our inquiry. From personalised AI assistants we quickly moved to the broader economics of AI — circling back again and again to two themes: whether AI can ever replicate the human experience, and the friction between the utopian ideals we project onto it and the gravitational pull of capitalism. I have sought to recount our discussion on these themes as accurately as memory allows, adding only modest(?) embellishment where it aids narrative coherence. On AI and human interaction: As someone quoted: “Do you know what it smells like in the Sistine Chapel?” (Good Will Hunting). The line reminds us that knowledge can be learned, but wisdom must be lived. Does an AI know what it is to be human? Can it ever truly understand the human experience? We are not just a collection of data points; we are a tapestry of emotions, experiences, and connections. AI can analyse patterns, but can it ever grasp the essence of what it means to be human? Human art matters because it exposes something fragile. To create is to risk oneself: to bleed, to reveal, to offer a fragment of the human condition for others to recognise. AI can imitate the form, but form without risk is mimicry. Can imitation ever supply the soul? Perhaps all we truly crave, as a species, is to be seen — to connect with each other. Yet history suggests authenticity is not always required. Chess engines long ago surpassed every human master, yet millions still prefer to watch people play. Calculators did not end mathematics; they expanded it, making it more ambitious and more accessible. Technology rarely erases human practice — but it does reframe it. The question is not only whether we can connect with AI as with another human, but whether we will still insist on doing so. AI companions and “digital girlfriends” already suggest that some are content with machine-mediated intimacy. The unsettling prospect is not that AI lacks a soul, but that we may cease to care. What happens when a generation grows up regarding “connection enough” as something delivered by code? If we defer not only thought but also empathy, attention, and intimacy to our machines, what remains distinctly human? We shape our tools, and thereafter our tools shape us (Culkin). On AI and economics: AI will not escape the gravitational pull of commerce. As today’s internet is financed by advertising, it is inevitable that AI systems will be bent to the same imperatives — nudging our choices, steering our attention, and monetising our interactions. Already we see the first signs: an Alexa Show inserting shopping prompts directly into the home. For all our talk of AI safety and ethics, it is commerce that drives development. But once human labour itself is displaced, what then? A utopia of leisure where we are free to follow our passions? Or a dystopia in which a minority, owning the means of cognition itself, consign the rest of us to redundancy? Could a society without labour even cohere — or would it demand a wholesale reinvention of politics, economy, and democracy itself? As we tried to weave our threads together into something coherent, this was the question that seemed most fertile for further debate. What is the politics of AI? What would a political and economic system look like that could accommodate these changes? How do we ensure that the benefits of AI are shared equitably, rather than concentrating power and wealth in the hands of a few? Our discussions were rich, unsettling, and illuminating, tracing both promise and peril. Yet the future owes no loyalty to our prophecies. The greater danger is not that AI will fail to know us, but that, in its shadow, we will lose the thread of ourselves. In the afternoon: Having solved the future of AI before lunch, we turned in the afternoon to the far more mundane task of reinventing the games industry. One of the industries evergreen obsessions is how to make characters and narratives more believable. As games grow ever more immersive, the hunger for deeper storytelling only intensifies. Yet, despite extraordinary technical progress, this is the frontier we keep failing to cross — because the obstacle is less technical, and more human. The costs of creating content are crushing. Large language models offer a tantalising shortcut: a machine that might spin endless dialogue, branching quests, even whole worlds on demand. But this promise comes bound up with limitations so profound they may be unsolvable with current methods. My own curiosity lies in a hybrid approach: using generative AI not as an all-purpose author, but as a tool to help construct traditional symbolic systems — frameworks that could give structure and coherence while still leaving room for human craft. If it worked, it might nudge us forward in this arena without the problems that come with the other approaches. But this is not a conversation one can leap into lightly. It demands deep knowledge of how games are actually made, tested, and sold, as well as a sober reckoning with both the failures and the potential of LLMs. Much of our discussion was spent simply reaching the starting line. The groups diversity produced fresh perspectives, but the depth of the subject meant we could not advance far in the time available. What did become clear was this: the problem is not just technical, it is communicative. If this debate is to progress, the challenge must be articulated in a way that is accessible beyond a narrow circle of experts. That, I realised, is the real work still ahead. Post Script: We live in a time of unprecedented change (at least in living memory). The world has enjoyed relative peace up until about 2020 but it feels like the geopolitical sands are shifting in a once-in-a-century phenomenon and such change has wide-ranging global political and economic implications for modern society broadly, but specifically within technology. This scenario is quite relevant to some of our discussions; the place and role of AI in our society is hard to gauge when our society is going through some fairly tectonic shifts. I think it will be a job for historians in the future to determine whether the emergence of advanced AI and these changes are correlation or coincidence, but it is clear that we cannot evaluate and analyse AI within a vacuum. The wider context is key here and that context is both nebulous and shifting all the time. Perhaps AI can support such a perspective in ways that one (or many) human minds cannot comprehend at once? Previous Next Previous Next

< Back Coming up: iGGi Open Day! Coming Up: iGGi Open Day! To all prospective Applicants to iGGi: Don’t forget to register for our *in-person* Open Day (if you can make it) >> iGGi OPEN DAY << at University of York (Village East) and Queen Mary University of London (Whitechapel Campus) Tuesday 10 Jan 2023, 12:00-15:30 Come along to meet iGGi Researchers/Supervisors/Staff in person Schedule + REGISTRATION: >> for York here: https://tinyurl.com/yvwpp5bz >> for London here: https://tinyurl.com/bdcr3xfy We look forward to meeting you! *The photo is from our recent Game AI Group December Party!! at Empire House (QMUL Whitechapel Campus) Previous 20 Dec 2022 Next

< Back GAIG Meetup The recent Game AI Meetup took place on 01 March 2023. Talks and presentation included: Jakob Foerster (University of Oxford, UK): Opponent-Shaping and Interference in General-Sum Games Original talk abstract: In general-sum games, the interaction of self-interested learning agents commonly leads to collectively worst-case outcomes, such as defect-defect in the iterated prisoner's dilemma (IPD). To overcome this, some methods, such as Learning with Opponent-Learning Awareness (LOLA), shape their opponents' learning process. However, these methods are myopic since only a small number of steps can be anticipated, are asymmetric since they treat other agents as naive learners, and require the use of higher-order derivatives, which are calculated through white-box access to an opponent's differentiable learning algorithm. In this talk I will first introduce Model-Free Opponent Shaping (M-FOS), which overcomes all of these limitations. M-FOS learns in a meta-game in which each meta-step is an episode of the underlying (``inner'') game. The meta-state consists of the inner policies, and the meta-policy produces a new inner policy to be used in the next episode. M-FOS then uses generic model-free optimisation methods to learn meta-policies that accomplish long-horizon opponent shaping. I will finish off the talk with our recent results for adversarial (or cooperative) cheap-talk: How can agents interfere with (or support) the learning process of other agents without being able to act in the environment? Vanessa Volz ( modl.ai ): Establishing Trust in AI-based Tools for Game Development Original talk abstract: AI-based tools to support the game development process have long been a topic in Game AI research, with popular publications in testing, churn prediction, asset, level and even game generation. However, the adaptation of these techniques from the games industry has been hesitant at best: The small-scale and simplified examples researchers use to demonstrate their work understandably only seldom convince the industry to risk investing in AI tools. In this talk, I will speak about my experience establishing trust in AI-based tools to support creative processes in game development. Having worked on this topic in both industry and academia, I will address issues ranging from establishing a common language and explaining AI behaviour to issuing performance guarantees via benchmarking and theoretical analysis. Mike Preuss (Leiden University, The Netherlands): In the eye of the storm? Where are we going with game AI? Original talk abstract: Looking back at the last 10 years of research in Game AI we find that Big Tech research has shaken up things quite a lot. A number of challenges were resolved in record time (Go, StarCraft, etc) and AI algorithm development is probably still increasing in speed. However, it seems that the use of AI in game-making has not changed that much, and academic research often opts for "smaller problems", slowly turning towards Human-Centered AI as possibly most important general research direction. How can we approach the next leap predicted by Alex Champandard 10 years ago of really intelligent game AI? And where would we want that? Mike presents some inconclusive thoughts and ideas on future developments. The Game AI Meetup takes place several times a year. To sign up and receive updates, please register/join here: https://www.meetup.com/game-ai-meetup-gaim-of-london/ Previous 1 Mar 2023 Next

< Back On the Behavioural Profiling of Gamblers Using Cryptocurrency Transaction Data Link Author(s) OJ Scholten Abstract More info TBA Link

< Back Diversity maintenance using a population of repelling random-mutation hill climbers Link Author(s) R Volkovas, M Fairbank, D Perez-Liebana Abstract More info TBA Link

< Back Studying General Agents in Video Games from the Perspective of Player Experience Link Author(s) C Guerrero-Romero, S Kumari, D Perez-Liebana, S Deterding Abstract More info TBA Link

< Back Why game designers should study magic Link Author(s) S Kumari, S Deterding, G Kuhn Abstract More info TBA Link

< Back IGGI 2021 Conference start The IGGI 2021 Conference will kick-start tomorrow with a promising looking schedule of exiting speakers for our Panels, 18 Talks, 2 Workshops, and the traditional IGGI Buzz Talks, all spread over two days. Don't miss out and join us online on Gather.Town Previous 7 Sept 2021 Next