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< Back Dr Sokol Murturi Goldsmiths iGGi Alum AI for game design: learning from designers For my PhD I am investigating how AI can help developers by learning to generate content in a similar fashion to the developers themselves. I envision a framework based on reinforcement learning, where an AI can learn a design policy for some content domain (e.g., FPS maps or platformer levels) by observing human designers. The AI would learn to take particular design actions in certain kinds of content states. Recent research into reinforcement learning has shown it is a powerful framework for developing complex agent behaviours and I believe there is a lot of potential to apply this work to game design. How would a human and artificial designer interact? Assume that an AI has learned to design a specific kind of content, such as a house, by observing human designers at work. A human designer could then partially develop some new content, and ask the AI to suggest some variations on it (see figure below), with both AI and human iterating on the design in a mixed-initiative interaction. The AI could learn from feedback from both the human designer and playtesting. As human feedback may not produce enough data for effective learning, the AI could perhaps extend this with data from simulated playtests. Game design decisions are often made with an expectation of how the player will react, and I could also look at how player models could be incorporated into the AI designer. In a reinforcement learning approach, the state could represent content+player, and the AI could learn to take design actions aimed a specific types of player. Developers could use this framework to develop content targeted at an individual player's style. Moreover, if the AI has learned something about how the human designer creates content, it can then be used live during the game to modify game elements in response to player interaction. Developers could set up modular levels, giving the AI the ability to adapt certain areas with content generated specifically to match the player. smurt001@gold.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next

< Back Dr Lina Gega University of York Supervisor Qualified both as a nurse and a psychological therapist, Lina is a senior member of the Mental Health and Addictions Research Group (MHARG) at the University of York, where she leads research under the Digital Mental Health Theme. She has published widely on computer-based therapies and virtual environments. Lina's work on technology-mediated interventions and training formed an impact case study was submitted to 2014 Research Excellence Framework as part of Psychology, Psychiatry and Neuroscience. Lina’s current work focuses on interventions to improve health and quality of life for children and young people with mental health problems. She has led the development and evaluation of a purposeful game to treat phobias in children, and of an innovative virtual environments system to assist psychological therapy and skills training. She co-leads the digital theme for the Closing the Gap (CTG) Network, funded by UK Research and Innovation (UKRI). The Network’s digital theme explores how technologies, including gaming, can be used to improve the physical health of people with severe mental illness, especially schizophrenia and bipolar affective disorder. An experienced University teacher, supervisor and examiner, Lina welcomes students with a design, engineering or behavioural sciences background who are interested in applied games research in the field of mental health, with a focus on: development and ‘proof-of-concept’ studies of purposeful games to improve mental health outcomes and social communication skills in children and young people. adaptation and evaluation of gamified applications to improve physical health outcomes with people whose motivation and information processing are affected by severe mental illness. Research themes: Game Design Games with a Purpose Player Experience Gamified Mental Health Interventions lina.gega@york.ac.uk Email Mastodon https://www.york.ac.uk/healthsciences/our-staff/lina-gega/ Other links Website LinkedIn BlueSky Github Themes Applied Games Player Research - Previous Next

< Back Dr Yizhao Jin Queen Mary University of London iGGi Alum Currently a student at Queen Mary University of London (QMUL), I have delved deep into the realms of artificial intelligence and game design. With a passion for understanding the complexities behind real-time strategy (RTS) games and their dynamic, unpredictable nature, I have committed myself to contribute novel insights to this domain. Research: My primary research area is Hierarchical Reinforcement Learning (HRL) for Real-Time Strategy (RTS) games. RTS games, known for their intricate mechanics and vast decision spaces, present a formidable challenge for traditional AI approaches. By employing HRL, I aim to develop agents that can not only understand the multi-layered tactics and strategies of these games but also learn to adapt to ever-changing game scenarios efficiently. The main objectives of my research are: Better Generalization: To create agents that can seamlessly transition between different RTS games or various maps within the same game without extensive retraining. This involves understanding common strategic threads across multiple game domains. Efficient Training: RTS games are inherently time-consuming due to their vast decision spaces and prolonged gameplay. My research seeks ways to optimize the training process, ensuring that AI agents can learn faster and with fewer computational resources. acw596@qmul.ac.uk Email Mastodon Other links Website LinkedIn BlueSky https://github.com/decatt Github Supervisors: Prof. Greg Slabaugh Prof. Simon Lucas Themes Game AI Previous Next

< Back Prof. Simon Lucas Queen Mary University of London iGGi Co-Investigator Supervisor Simon Lucas is a professor of Artificial Intelligence and Head of the School of Electronic Engineering and Computer Science at Queen Mary University of London where he also heads the Game AI Research Group. He holds a PhD degree (1991) in Electronics and Computer Science from the University of Southampton. He is the founding Editor-in-Chief of the IEEE Transactions on Games and co-founded the IEEE Conference on Games. His research involves developing and applying computational intelligence techniques to build better game AI, use AI to design better games, provide deep insights into the nature of intelligence and work towards Artificial General Intelligence. He is the QMUL lead for the EPSRC-funded CDT in Intelligent Games and Game Intelligence (IGGI). He has supervised more that 15 PhD students to completion, most of them in Game AI. Research themes: Game AI Agents (RL, Monte Carlo Tree Search, Rolling Horizon Evolution) Learning Forward Models Automated Game Design, Procedural Content Generation Game AI for real-world problem solving simon.lucas@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/profiles/lucassimon.html Other links Website LinkedIn BlueSky https://github.com/simon-lucas Github Themes Game AI - Previous Next

< Back Prof. William Latham Goldsmiths iGGi Co-Investigator Supervisor William Latham is well known for his pioneering organic computer art created in the 80s and early 90s whilst a Research Fellow at IBM in Winchester. In 1993 he moved into Rave Music setting up a small studio in Soho, creating album covers, stage designs and videos for bands including The Shamen for three years. He then worked for ten years as Creative Director and CEO of a large computer games development company, with studios in London and Brighton, creating PC and console games published by Vivendi Universal, SONY and Warner Bros. Among the games he has produced were Evolva for Virgin Interactive, and the hit game The Thing for Vivendi Universal for Xbox, PlayStation, PC. based on the famous John Carpenter horror movie set in Antarctica. In 2007, he became a Professor in Computing at Goldsmiths, where he works on research projects with Imperial College, York University, and the Oxford Weatherall Institute. His recent "Mutator VR" Sci-Fi art experience developed at Goldsmiths for the HTC Vive has been exhibited to much acclaim in galleries and museums Shanghai, Venice, Kyoto, Dusseldorf and St. Petersburg. William was an undergraduate student at Christchurch College, Oxford University, and a postgraduate student at The Royal College of Art. His book on interactive evolutionary design, “Evolutionary Art and Computers” is cited as a leading publication in this domain. He is Director of SoftV Ltd, a company which develops Neuroscience Patient mobile Games Apps for the NHS in Unity, and is a co-founder of London Geometry Ltd. w.latham@gold.ac.uk Email Mastodon https://www.mutatorvr.co.uk Other links Website https://www.linkedin.com/in/william-latham-757326/ LinkedIn BlueSky Github Themes Creative Computing Immersive Technology - Previous Next

< Back Dr Charline Foch University of York iGGi Alum Charline first came to the UK in 2011 to study English and Film Studies at King’s College London, before going on to a MSc in Film, Exhibition and Curation at the University of Edinburgh. By chance, accident or fate, she stumbled into the games industry, working in an independent game studio in Berlin, where she touched upon customer support, community management, content writing and QA for a new MMORPG. This experience gave her the push to start a PhD in video games. In her spare time, she is an avid film viewer, volleyball player, and amateur artist. Charline’s research focuses on how people conceptualise failure, with an emphasis on its perceived positive, desirable effects on player experience. Throughout her PhD, she has conducted research among video games players to gain a better understanding of what they perceive as the purpose and value of failure in the games they play; and conducted research among video games developers to gain a better understanding of what processes, obstacles, and ideas go into the design and implementation of failure in their games. With a focus on single-player, more narrative-driven games, she has used this research to design a cards-based design toolkit to support game designers in approaching the question of fail states and player experience in the early stages of the game development process, helping them reflect on the intersection between failure, game mechanics, storytelling, and player experience when working on their games. Aside from her PhD, Charline has also worked with the Digital Creativity Labs on the PlayOn! project, a European project gathering 9 theatres across Europe working on immersive technologies (VR, AR, apps for audience participation...) and theatre productions. During her time at PlayOn!, she has worked on the connections between the games industry and the performance arts, investigating how technology, game design principles, and theatre can work together, and what barriers practitioners face when attempting to reconcile all sides in a single production through experimentation and collaboration. charline.foch@york.ac.uk Email https://mastodon.gamedev.place/@chafoch Mastodon https://charlinefoch.carrd.co Other links Website https://www.linkedin.com/in/charline-foch-97196663 LinkedIn BlueSky Github Supervisor: Dr Ben Kirman Featured Publication(s): “The game doesn't judge you”: game designers’ perspectives on implementing failure in video games “Slow down and look”: Desirable aspects of failure in video games, from the perspective of players. Themes Design & Development Player Research - Previous Next

< Back Dr Kyle Worrall University of York iGGi Alum Available for post-PhD position Kyle is a final-year PhD researcher at the Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI) at the University of York, where his work centers on pioneering deep learning-driven music tools for video game composers. In addition to his research, Kyle is a Lecturer in Games Programming at Edge Hill University, where he encourages the next generation of game developers to appreciate the critical role of audio in interactive experiences. Beyond academia, Kyle is the Founder of Cocreative Technology, an ethical AI music startup on a mission to empower musicians with cutting-edge, AI-driven tools that amplify creative expression, combat burnout, and elevate the emotional depth of game soundtracks. Kyle's research explores how deep learning and generative AI can enhance the creative workflow of video game composers, and improve the experience of players by reducing musical repetition. His work spans symbolic music generation, and real-time adaptive music systems, aiming to improve the emotional expressiveness and of game audio. His recent publications focus on deep learning models for interactive music authoring, expressive performance modelling, the ethical considerations in AI-assisted creativity, and the integration of neural networks with procedural music generation in games. By combining symbolic AI and audio signal processing, Kyle develops tools that support composers in ideation, iteration, and adaptive composition, while remaining transparent and musically intuitive. An experienced speaker, Kyle has presented at leading industry events, including Airwiggle's AirCon 2025, Game Sound Con 2024, Audio Dev Con 2024, the Global Arts and Psychology Symposium 2023, the Play Again Symposium 2024, and the Digital Creativity, Industry and Culture Conference 2022. He is also a regular contributor to the IGGI Conference (2020–2024), and has been featured in TechCrunch, Dazed, The Story of the Sound, and The Audio Programmer podcast, as well as featured on a panel with leaders in game audio from Meta and Sony. kyle.worrall@york.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/kyleworrallmusic/ LinkedIn BlueSky https://github.com/KJWAudio Github Supervisors: Dr Jon Hook Dr Tom Collins Dr Josh Reiss Featured Publication(s): Final Fantasy VII Remake Music Redesign for Evolved Expectations Across Console Generations Considerations and Concerns of Professional Game Composers Regarding Artificially Intelligent Music Technology Comparative evaluation in the wild: Systems for the expressive rendering of music Reflection Across AI-based Music Composition The Ethics of Creative AI Themes Creative Computing Game Audio https://www.youtube.com/watch?v=m5vCJCB2-2A https://www.youtube.com/watch?v=AllYuKKxks8 Previous Next

< Back Nirit Binyamini Ben Meir Queen Mary University of London iGGi PG Researcher Available for placement Nirit Binyamini Ben-Meir is a designer/ artist based in London. Her work explores the interconnection between society, technology and ecology. She is an Associate Lecturer at the Royal College of Art London, where she gained her MA in Information Experience Design. She has a professional background in visual communication and interaction design. She uses participatory installations, digital tools and responsive plants to create experiences for humans to interact with their biosphere. She combines ecological systems with technology to challenge human perception and provoke thought about bioethics, power relations, and the Anthropocene implications. Nirit’s main research interests are around More-Than-Human Interactions and the integration of living organisms into digital interactions. She investigates how these hybrid interactions may help mediate relatable, sensory experiences with plants and influence people's attitudes towards ecological stewardship. She is developing the Bio-Digital Garden concept, which combines computational elements and living moss, a responsive plant that gives qualitative visual feedback to changes in its environment in real-time. Her exploration focuses on the potential of using human-computer-plant to identify current weak points in pro-environmental behaviour and care for non-human entities, as well as influence people's perceived accountability through tangible feedback, bridging time-scale gaps, and generating a sense of urgency. n.binyaminiben-meir@qmul.ac.uk Email Mastodon https://niritbin.com/ Other links Website LinkedIn BlueSky Github Supervisors: Prof. Sebastian Deterding Featured Publication(s): Domestic Cultures of Plant Care: A Moss Terrarium Probe Experience as a transformational practice Design Methods for Accessing the Pluriverse Forging new narratives Themes Applied Games Creative Computing Design & Development - Previous Next

< Back Michael Aichmüller Queen Mary University of London iGGi Alum My background lies in physics and statistical mathematics with a later specialization in optimization in the fields of Reinforcement Learning (RL) and Causal Inference. My first encounters with RL occurred during my Masters when studying how to create strong policies in perfect information games using algorithms, such as MinMax, MCTS, DQN, and later AlphaZero variants. My favorite game application remains the board game ‘Stratego’. In the meantime I investigated the estimation of causal parents influencing a target variable from interventional datasets for my Master’s thesis. Specifically, how well Deep Learning estimations could replace exponentially scaling graph search methods with approximations requiring only polynomial runtime. A description of Michael's research: My research focuses on the state-of-the-art in game-playing solutions for imperfect information games (think games like Poker, Stratego, Liar’s Dice etc.). I am particularly interested in the application of No-Regret (and related) methods which seek to learn those actions that provided the most benefit (or least regret) compared to the benefit all possible actions provided on average. These methods learn such via iterative play to find a Nash-Equilibrium (NE), a game-theoretic concept comparable to an optimal policy known from Single-Agent RL, but for all partaking players at once. Particularly, variants of Counterfactual Regret Minimization (CFR) remain the state-of-the-art algorithms for computing NEs in 2-player zero-sum games due to their success in tabular form so far. Yet, prohibitive complexity and memory scaling bars them from large-scale applications. Hence, research of recent years seeks to couple CFR (and other No-Regret methods) with function approximation, such as Deep Learning, to scale up the size of applicable games with already notable successes (Deepstack, Libratus, Pluribus, DeepNash). My research seeks to contribute to this endeavour by first analyzing the specifics of established methods and finding ways to introduce Hierarchical RL concepts to No-Regret learning. Please note: Updating of profile text in progress m.f.aichmueller@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/michael-aichmueller/ LinkedIn BlueSky https://github.com/maichmueller Github Supervisor(s): Prof. Simon Lucas Dr Raluca Gaina Themes Applied Games Game AI - Previous Next

< Back Janet Gibbs Goldsmiths iGGi Alum Janet is exploring how multi-modal perceptual feedback contributes to a player's sense of presence in the virtual world. Jaron Lanier described Virtual Reality (VR) as the substitution of the interface between a person and their physical environment with an interface to a simulated environment. This interface is of particular significance in understanding how presence depends on the nature, extent and veridicality of our sensorimotor interaction with the virtual environment, and how that relates to our normal engagement with the real world. In practice, only selected parts of the interface are substituted - we are never fully removed from our physical environment. Our perceptual apparatus evolved to make sense of changing sensations in multiple modalities originating naturally and coherently from the same event or percept. By contrast, in VR, individually crafted feedback using different technologies for each modality are coordinated to appear as if from a single source. VR benefits from a long history of visual and audio technologies, developed in harness for virtual experiences from cinema to computer games. Haptics is a relative newcomer that must be blended with them to create coherent multimodal perceptual experiences. Additionally, haptics is closely related to proprioception, and to the wide range of tactile senses—texture, heat, pain etc—that current VR systems do not address. Building on sensorimotor theory of perception, Janet aims to establish how our perceptual system responds to multi-modal feedback that almost, but not quite, matches what we are used to, in making sense of the simulated environment of VR. JGIBB016@gold.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Investigating Sensorimotor Contingencies in the Enactive Interface A comparison of the effects of haptic and visual feedback on presence in virtual reality Novel Player Experience with Sensory Substitution and Augmentation Investigating sensorimotor contingencies in the enactive interface Themes - Previous Next

< Back Dr Jon Hook University of York Supervisor Jon Hook is a Senior Lecturer (equivalent to an Associate Professor) in Interactive Media in the Department of Theatre, Film, Television and Interactive Media at the University of York. His research is situated in the field of Human-Computer Interaction (HCI) and explores the design and development of new interactive media content forms and tools to support their creation. This research combines his deep interest in new forms of interactive technology and media with empirical, theoretical and methodological perspectives, in the human-centred design of novel interfaces and interaction techniques for a broad range of artistic and everyday creative practices. His current research is focused on the design and development of new forms of responsive and immersive media content, with a particular interest in data-driven storytelling. He was recently the principal investigator of the EPSRC funded Perspective Media: Personalised Video Storytelling for Data Engagement project. He also a co-investigator of the InnovateUK WEAVR: Pioneering Fully Integrated Cross-Reality Spectator Experiences in Esports and Beyond immersive experiences demonstrator and the Digital Creativity Labs – a £4m EPSRC, AHRC and InnovateUK funded research centre exploring impact-driven research in the creative industries. He was also previously Co-I of the AHRC Within the walls of York Gaol: Memory, Place and the Immersive Museum the AHRC Digital Creativity for Regional Museums: Immersive Experiences Smart Commissioning Toolkit. He is especially interested in supervising students who’d like to do HCI research that involves making and evaluating new interactive media experiences. Some example topic areas that he might be the right supervisor for include, but aren’t limited to: Games to support broader data engagement and literacy Data-driven storytelling in, and about, games The intersection between games and interactive documentary film Responsive and interactive video storytelling in games The space where theatre and games converge Cultural heritage engagement using games Research themes: Game Design Games with a Purpose E-Sports Player Experience jonathan.hook@york.ac.uk Email Mastodon https://www.jonhook.co.uk Other links Website https://www.linkedin.com/in/jonathan-hook-641b597/ LinkedIn BlueSky https://github.com/jonathanhook Github Themes Applied Games Esports Player Research - Previous Next

< Back Dr Martin Balla Queen Mary University of London iGGi Alum Before starting his PhD Martin studied Computer Science at the University of Essex. His main interest is artificial intelligence and its application to all sort of problems ranging from computer vision to game AI. He likes spending his spare time with various activities which mainly involves reading, playing video games and skateboarding. Martin's PhD thesis focuses on Reinforcement Learning agents that can adapt to changes in the reward function and/or changes in the environment. His work investigates how agents can transfer their knowledge to changes in the environment, such as new rewards, levels or visuals. Outside of his main research direction, Martin is involved with the Tabletop games framework (TAG), which is a collection of various tabletop games implemented with a common API with a focus on various game-playing agents (including RL). TAG brings various challenges to RL agents compared to search-based agents, such as complex action spaces, unique observation spaces (various embeddings), multi-agent dynamics with competitive and collaborative aspects, and lots of hidden information and stochasticity. m.balla@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/martinballa LinkedIn BlueSky https://martinballa.github.io Github Supervisors: Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Illuminating Game Space Using MAP-Elites for Assisting Video Game Design PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games TAG: Pandemic Competition Task Relabelling for Multi-task Transfer using Successor Features TAG: A tabletop games framework Design and implementation of TAG: a tabletop games framework Evaluating generalisation in general video game playing Evaluating Generalization in General Video Game Playing Analysis of statistical forward planning methods in Pommerman Themes Game AI - Previous Next