< Back Dr Ryan Spick University of York iGGi Alum Deep Learning for Procedural Content Generation in Virtual Environments Ryan Spick is a PhD student with a computer science background, working on methods to improve how content (models, terrain, assets etc.) is created with an autonomous focus, with the main focus on generative deep learning to augment real-world data through a series of neural network layers to learn unlying properties of these data. Ryan has published a variety of papers around his main topic of generating content, such as terrain generation using generative adversarial networks and 3D voxel coloured model generation, to collaborations on other topics using deep learning, such as death prediction in a multiplayer online game and applying a recent map-elites algorithm. He has also worked with several leading industry researchers/games companies to further develop his research skill.If you have any ideas or collaboration opportunities please get in contact through any of the mediums below. Please note: Updating of profile text in progress Email ryan.spick@hotmail.co.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): System and Method for Point Cloud Generation System and method for training a machine learning model Robust Imitation Learning for Automated Game Testing Behavioural Cloning in VizDoom Utilising VIPER for Parameter Space Exploration in Agent Based Wealth Distribution Models Human Point Cloud Generation using Deep Learning Naive mesh-to-mesh coloured model generation using 3D GANs Realistic and textured terrain generation using GANs Procedural Generation using Spatial GANs for Region-Specific Learning of Elevation Data Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Time to die: Death prediction in dota 2 using deep learning Themes Game AI - Previous Next

< Back Dr Shringi Kumari University of York iGGi Alum Shringi is a seasoned game designer with more than nine years of experience making games for companies including EA, Zynga, Bigpoint, and Wooga. She became a researcher four years ago, wondering how game designers can take inspiration from other creative fields. In her PhD, she is now studying how stage magic can be translated to games for creating believable illusions of choice and moments of surprise. She continues to consult as a game designer for companies and has started a lecturership in game design at University of East London. In the past years she has spoken about game design across the world at a number of known platforms: Indiecade Europe, Develop, Game Happens, SOMA Chicago, GDC India to count some. As a creative, she engages in working on disruptive design both in games and beyond. Her work reflects her Indian background and discusses universal issues of identity, need for diversity and the idea or illusion of home. She has recently published her debut poetry collection,“The Saree Shop” and has featured in a short story anthology with her story ”Garden of Vaginas”. Shringi is supervised by Dr Sebastian Deterding (York) and Dr Gustav Kuhn (Goldsmiths). Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): The role of uncertainty in moment-to-moment player motivation: a grounded theory Why game designers should study magic Investigating uncertainty in digital games and its impact on player immersion Studying General Agents in Video Games from the Perspective of Player Experience The Magician's Choice: Providing illusory choice and sense of agency with the Equivoque forcing technique. Design Inspiration for Motivating Uncertainty in Games using Stage Magic Principles Themes Player Research - Previous Next

< Back Dr Claudio Guarnera University of York Supervisor You can get more out of your site elements by making them dynamic. To connect this element to content from your collection, select the element and click Connect to Data. Once connected, you can update it anytime without affecting your design or updating elements by hand. Add any type of content to your collection, such as rich text, images, videos and more, or upload it via CSV file. You can also collect and store information from your site visitors using input elements like custom forms and fields. Be sure to click Sync after making changes in a collection, so visitors can see your newest content on your live site. Email claudio.guarnera@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing - Previous Next

< 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. Email smurt001@gold.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

< Back Sahar Mirhadi University of York iGGi PG Researcher Available for post-PhD position Sahar Mirhadi is a final-year PhD researcher investigating how video games support during challenging times. Her contributions have been published in the Proceedings of the ACM Conference on Human-Computer Interaction, and she has presented at Devcom on transforming the complexity of turn-based games into a strategic advantage. She is also a passionate Magic: The Gathering player, collaborating with competitive Magic team Worldly Counsel to convert tournament insights into a deeper understanding of player motivations and team dynamics. Sahar is also a Safe In Our World Ambassador, a recipient of the Magic: The Gathering New Perspectives Grant for Marginalised Players, and a member of the Birds of Paradise collective. A description of Sahar's research: Sahar's PhD research project investigates the specific aspects of games that facilitate coping for players during difficult life experiences. Building on earlier work that mapped broad links between game aspects and coping strategies, Sahar’s first study showed that games can support a variety of coping strategies, including emotion-focused, avoidance, and meaning-focused coping. However, questions remained about how these effects occur across different gaming contexts. To address this, her second study employed in-depth interviews and a grounded theory approach with players of Disco Elysium, Darkest Dungeon and Stardew Valley. The findings led to the development of the Games as Dynamic Coping Systems theory, which posits that specific aspects of video games scaffold a diverse range of coping strategies for players facing personal difficulties. The model highlights the dynamic interplay between what the player brings (e.g., prior experiences, needs, skills) and what the game provides (such as Narrative, Game Environment and Character Interactions). Through this interaction, players develop coping strategies, and the outcomes from coping feed back into their ongoing gaming and life experiences. While the grounded theory offered a deeper understanding of how specific game aspects support various coping strategies, it also revealed a gap: the temporal dynamics of coping. Sahar’s ongoing work aims to explore how players transition between coping strategies over time and what factors shape these transitions. Her overall aim is to provide a deeper understanding of specific aspects within games that support coping, shedding light on the potential benefits and limitations of video games during times of difficulty. Email sm2904@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Alena Denisova Dr Jo Iacovides Themes Player Research https://www.youtube.com/watch?v=0nTTCR25O0Y Previous Next

< Back Francesca Foffano University of York iGGi PG Researcher Available for post-PhD position Francesca is finalising her PhD at the University of York, specialising in UX, player experience and design. Their work spans game experience (e.g. getting stuck), safeguarding the design's impact on players (e.g. emotional accessibility), design recommendations (e.g. emotional design) and game development (e.g. adaptive games). They primarily use qualitative research and mixed methods to gain an in-depth understanding of the player experience. They are currently open to collaborations with industry and academia for funding applications. A description of Francesca's research: When it comes to emotions in video games, players should feel like they are enthusiastically part of the experience. However, at times, players risk feeling forced or overwhelmed. So, how to design these experiences correctly? Through a dual approach, I explore how to design emotional experiences at their extremes. On the one hand, I examine which design components create recognisable emotional experiences. On the other hand, I examine how design can overwhelm players to the point where they struggle to finish a game, as the design makes it impossible for them to process the emotions presented. Email ff716@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Featured Publication(s): Artificial intelligence across europe: A study on awareness, attitude and trust Disability tax in gacha games: the social cost of hidden expenses. Do Not Play With My Emotions. Design for Emotional Accessibility A Survey on AI and Ethics: Key factors in building AI trust and awareness across European citizens. When Games Become Inaccessible: A Constructive Grounded Theory on Stuckness in Videogames Artificial intelligence across europe: A study on awareness, attitude and trust Investing in AI for social good: an analysis of European national strategies European Strategy on AI: Are we truly fostering social good? Changes of user experience in an adaptive game: a study of an AI manager Themes Player Research - https://www.youtube.com/watch?v=v8xdnkjVL2c Previous Next

Partners (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 Partners We are excited to be collaborating with a number of industry partners. iGGi works with industry in some of the following ways: Researcher Industry Knowledge Exchange - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the researcher and their industry partner. Researcher Sponsorship - for some of our researchers, 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! Check out our Industry Info page here to see these types of collaboration described in more detail. 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. 22 Cans AI and Games Autistica BT BetaJester Limited BiG BlitzGame Studios Bossa Studios British Broadcasting Corporation BBC British Games Institute (BGI) CBT Clinics COMIC Research Carnegie Mellon University Cooperative Innovations Creative AI Creative Assembly Die Gute Fabrik Digital Catapult Dubit Limited Durham University ESL UK Electronic Arts (EA) Enigmatic Studios Falmouth University Fluttermind LLC

< Back Rokas Volkovas Queen Mary University of London iGGi Alum Application of Neuroevolution to General Video Game Playing In the field of artificial intelligence, great advancements in developing AI capable of playing specific games has been made over last few decades. Over the years, the potential of General Game Playing (GGP) AI, was realized, and thus a new area of research was spawned, focusing mainly on turn-based board games. Rapidly expanding, it was just recently extended to include video games and has morphed into General Video Game Playing (GVGP). The studies in this space of AI are highly attractive due to their solution capacity of being highly transferable. As the field is relatively new, there are many different paths to explore. Some effort has already been put into incorporating the established Genetic Algorithm techniques into the area. The goal of the proposed research is to further develop models using the more complex evolutionary algorithms to find generalist solutions to the problems exposed in GVGP. More specifically, the research will aim to discover the appropriate applications and the modifications necessary of approaches such as Competitive Coevolution, circumventing its drawbacks and evolving populations capable of playing multiple games. Furthermore, in addition to other methods it will be concerned with the application of models developing generalist memory on a slower scale evolution (compared to individual in a population) with continuous state perturbations, to find closer to optimum results - adapting networks of individuals to the fitness landscape. In order to reach the goals of the research a number of experiments will be conducted, using a select few video games as a base performance measure. Training the populations evolved will involve tuning the evolutionary operators as well as altering pre-designed system be- haviours to suitably compare the viability of applied procedures. The success of bridging EA with GVPG, along with its advantages and drawbacks in the field will be readily deter- mined, comparing the solutions found to those of other existing approaches. Specifically, the similarity of the behaviour in evolvability using genetic networks searching for solutions and learning theory, via neural networks, has recently been suggested. Evolution is defined to not have any foresight, but models were built showing how it can remember previously discovered solutions, which would imply that natural selection leans towards long term evolvability. Kostas Kouvaris et. al. further establishes the underlying equivalence of the approaches, applying machine learning techniques to improve the generalisation of EA. The generalization allows combining the features from previous experience to find individuals with new feature combinations, better adapted to unseen environments. Were the exploratory learning methods developed in EA to perform no less satisfactorily in the gaming industry environment, given enough sample data from a handful of well defined behaviours, the AI units could be trained to adapt to the new levels they are placed in. In theory, this would then translate to the same amount of effort producing a larger variety of content or, alternatively, producing the same amount of content with less effort, distributing the excess to other areas of development or eliminating it to lower the total production cost. Rokas is an MEng Electronic Engineering graduate from University of Southampton. Initially, pushed away from programming in school due to being taught Pascal, he realized its power in the compulsory C course in University. Applying the knowledge to building games caused the gradual shift from electronics to software development, with the 4th year modules all having the CS tag. During the undergraduate studies Rokas held the UKESF scholarship and did 2 summer internships at Imagination Technologies. Interests in game and software development got him researching neuroevolutionary machine learning for video games. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Automatic Game Tuning for Strategic Diversity Practical Game Design Tool: State Explorer Extracting learning curves from puzzle games Mek: Mechanics prototyping tool for 2d tile-based turn-based deterministic games Diversity maintenance using a population of repelling random-mutation hill climbers Themes Game AI - Previous Next

< Back Prof. Matthew Purver Queen Mary University of London Supervisor Matthew Purver is Professor of Computational Linguistics, and leader of QMUL’s Computational Linguistics Laboratory. His research has covered many aspects of natural language processing (NLP), with a £4m grant portfolio including projects on fundamental techniques like cross-lingual processing and incremental language understanding, and applications to news media, social media analysis and mental health diagnosis. His work has been covered by the Guardian, Telegraph, Independent, LA Times, NBC and Scientific American, among others. He is also a senior researcher at the Jožef Stefan Institute, Slovenia, and in 2011 he co-founded the company Chatterbox Labs Ltd. He is interested in supervising students with a background in NLP, linguistics or machine learning and an interest in analysis or generation of natural language. Research themes: Language in Games Game AI Computational Creativity Email m.purver@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game AI - Previous Next

< Back Stefan Stoican University of Essex iGGi Alum Understanding human crowd behaviour via virtual environments: feedback loop between games & research This project uses computer game experiments to explore decision-making in a virtual evacuation simulation. Can one be “saved by the gaze”? Currently, Stefan is investigating how innate social cognition components such as gaze-cuing might inform one’s egress. Do “Us versus Them” scenarios occur? He is also testing how one’s feelings of social identification with the surrounding crowd might modulate one’s risk-taking. Does hoarding prevent herding? Lastly, the project is looking at how cultural differences might affect egress time, when one insists to save personal possessions. More broadly, Stefan’s research concentrates on two key open questions in human crowd behavioural research. Firstly, how do social groups (that the player observes or is a member of) within the simulated crowd of agents affect both individual decision-making and the emergent behaviour of the crowd? Secondly, both empirical and virtual experiments of human crowds have not fully explored the effect of agent or player interactions with underlying landscape features (e.g. layout, signage, debris, large objects and other obstacles, etc). The outcomes of the experimental studies using real human participants will subsequently be used to develop more realistic decision-making and behavioural response algorithms and hence improve the behaviour of simulated agents in follow-on computer games. Stefan’s academic background may lie in Mathematics and Psychology, but his interdisciplinary mindset has constantly pushed him towards games and Computer Science. For his final Mathematics project, he designed an Android app that gamified teaching statistics. As part of his Psychology Masters degree, he investigated the potential benefits of MOBA games such as League of Legends with regard to visual attention. Currently, his extracurricular projects aim to explore video games’ effects on coping with trauma and on one’s perception of vulnerable groups, via commemorative gaming name choices or via in-game refugee storylines, respectively. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link 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 Email lina.gega@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Player Research - Previous Next

< Back Andrei Iacob University of Essex iGGi Alum Identifying Immersion in games using EEG and other measures (Industry placement at Sony SIE) The project aims to identify markers for immersion in player’s EEG signals. A few steps towards it include designing an experiment that reduces data noise and helps identify time frames for immersion during gameplay, recording EEG data among other “tests” to improve the accuracy of the state localization on a timeline. This research could prove useful for the games industry in a few ways: - it can provide tools for game testing (e.g. which parts of the game are immersive, which parts lack in that aspect) – thus making it easier to improve the game experience across the board; - it could also be used in making real-time adjustments to games (increase / decrease difficulty levels, pace, etc. to enhance the player’s immersion). Although the EEG data is the main focus of the project, it is not the only one. Correlations will be analyzed between different tests and in-game behaviors that should render even more information regarding the player’s state and mindset during gameplay. This information will be just as valuable and perhaps more readily available for widespread use in the near future. Andrei is a keen programmer and gamer. He graduated with a BSc (Hons) in Computer Science from the University of Essex. Andrei’s research interests are in the field of brain- computer interfaces and computer games. His hobbies include programming, gaming, guitar and skiing. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Player Research - Previous Next