< Back Dr David Zendle University of York Supervisor David Zendle is an active researcher into the effects of both video games and gambling, and is the author of several key references on the topic of video game monetisation. His most well-known publications deal with the potential effects of loot boxes. His recent work focuses on understanding the diversity of ways that video game play impacts wellbeing, and involves the analysis of large-scale datasets of player behaviour and spending. David is an academic affiliate of the Behavioural Insights Team and holds a research position within the NHS. He is particularly interested in building evidence-based policy in the domain of video game regulation, and has provided oral testimony on video game effects to a variety of government investigations across the globe. David is particularly interested in supervising students with an industry, economics, legal, or behavioural sciences background. He is interested in work on the following topics: The long-term effects of video game play (both positive and negative) Video game monetisation Video game regulation and policy Dark video game design Research themes: Game Analytics Game effects Game policy Email david.zendle@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game Data Player Research - Previous Next

< Back Dr Joseph Walton-Rivers University of Essex iGGi Alum Controlling Non-player characters. (Industry placement at Visteon) Within games non-player characters help to sell the world and give meaning to the player's experiences. These characters in games are presently not very believable and often lack the ability to interact with each other in meaningful ways. This work is looking at creating socially capable, believable agents to populate the worlds of role playing games. These agents need to be able to cope with player's actions and be capable of acting independent in the world. Joseph studied computer science at the University of Essex, obtaining a first class degree. During his study there he received two awards for academic achievement. After graduation he worked in the IT team of a company with offices across the United Kingdom where he developed and maintained their IT systems. Since starting IGGI he has worked on research involving co-operative agents working together to solve shared goals. He has a keen interest in programming and the Free Software movement. During his free time he enjoys strategy and puzzle games including Prison Architect, the Shadowrun series and Galactic Civilization 2. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Enhancing Programming Learning with AI-Generated Contextual Examples in Digital Creativity Peer Evaluation in Group Projects: Insight into Effective Student Critique and Feedback Evaluating the Effects on Monte Carlo Tree Search of Predicting Co-operative Agent Behaviour An Exploratory Analysis of Student Experiences with Peer Evaluation in Group Game Development Projects Student Perspectives on the Purpose of Peer Evaluation During Group Game Development Projects The 2018 Hanabi competition Hexboard: A generic game framework for turn-based strategy games Fireworks agent competition Evaluating and Modelling Hanabi-Playing Agents Controlling co-incidental non-player characters Monte carlo tree search applied to co-operative problems Distributed Social Multi-Agent Negotiation Framework For Incomplete Information Games Themes Player Research - 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

< Back Emily Marriott University of Essex iGGi Alum Automated Story Generation for Games Emily is researching automated story generation for video games, focusing on the use of Planning for real-time, dynamic generation. Ideally, the stories created will reflect choices made by the player during gameplay and will update continually throughout gameplay. The aim of this research is to create a system that could be easily utilised in the development of more adaptive games. This could improve player enjoyment, increase re-playability, and allow for the inclusion or exclusion of content that may only appeal to niche audiences. Emily’s current focus is on investigating story structures and pacing to create a template for generating good stories specifically for games that are consistent, well-structured and interesting. This involves studying the pacing requirements in existing games to establish what these are and how they differ the requirements for film and TV. The system will ideally be integrated with existing game-development tools and provide an easy-to-use interface to make the creation of adaptive games easier and quicker. The eventual goal is a full story-generation system would support both the creation of quests that emerge from story requirements and a game world that fits the environment required for the story. Emily graduated from Glyndŵr University with a BSc in Computer Games Development before completing an MSc in Computer Science at Oxford Brookes University. The substance of the MSc dissertation involved generating dungeon levels and quests using grammars based on the play style the player appeared to favour. Emily enjoys playing both tabletop and computer roleplaying games, especially ones in which player actions can have a dramatic effect on the game’s progression. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Player Research - 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 Email m.f.aichmueller@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Prof. Simon Lucas Dr Raluca Gaina Themes Applied Games Game AI - Previous Next

< Back Dr Charles Ringer University of York iGGi Alum Charlie Ringer is a researcher interested in applied Machine Learning with a focus on the ways in which we can use Deep Learning to model various facets of video games streams (e.g. stream highlights, emotional moments, in-game events, various streamer behaviours etc.). As such, his work spans many Machine Learning fields, such as Computer Vision, Affect Computing, and Natural Language Processing. His research has three motivating factors. Firstly, the challenge of how to fuse multi-view stream data (e.g. audio, web-cam footage, game footage, chat) into a single model, especially when considering the challenges of ‘in-the-wild’ data. Secondly, the untapped and bountiful data source that livestreaming represents, especially regarding the way in which streamers play games and interact with their audience. Thirdly, the exciting and emerging field of self-supervised learning which has the potential to utilise this abundance of livestream data. Charlie initially worked in the video games industry working mainly on the Magic: The Gathering - Duels of the Planeswalkers series of games before studying a BSc in Computer Science at Goldsmiths, University of London. After his BSc he joined IGGI, firstly at Goldsmiths and then at York. He was recognised as a finalist for the Twitch Research Fellowship 2019 for his research on livestream data. Email charles.ringer@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Machine Learning with Applications From Theory to Behaviour: Towards a General Model of Engagement Modelling early user-game interactions for joint estimation of survival time and churn probability Time to die 2: Improved in-game death prediction in dota 2 Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data Multi-Modal Livestream Highlight Detection from Audio, Visual, and Language Data Twitchchat: A dataset for exploring livestream chat Multimodal joint emotion and game context recognition in league of legends livestreams Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals Deep unsupervised multi-view detection of video game stream highlights Streaming behaviour: Live streaming as a paradigm for multi-view analysis of emotional and social signals Rolling Horizon Co-evolution in Two-player General Video Game Playing Themes Esports Game AI Game Data - Previous Next

< Back Alex Fletcher Queen Mary University of London iGGi Alum Alex Fletcher is a freelance audio engineer and junior game developer working on understanding the perceived flow and player experiences in mobile rhythm games and how a dynamic difficulty adjustment system would improve these experiences. The function of EEG and other biosensors as an additional measurement of player experience is of particular interest as further research in its use as an adaptive system. Other areas of research interest include game-based learning and games with a purpose. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Game Audio Player Research - Previous Next

< Back Dr Christian Guckelsberger Queen Mary University of London iGGi Alum + Supervisor Intrinsic Motivation in Computational Creativity with Applications to Games. (Industry placement at Splash Damage and Microsoft Research) This research investigates how we can engineer artificial systems that are creative in their own right. Christian addresses this challenge with computational models of intrinsic motivation (IM). Intrinsically motivated agents perform an activity for its inherent satisfaction rather than for some instrumental outcome. A classic example is to act in order to satisfy one’s curiosity. In both theoretical and applied studies, he demonstrates that models of IM can give rise to general, robust and adaptive creative systems. Christian has shown how models of IM can be used to create highly general non-player characters. Such characters can potentially be used in a wide range of games without previous knowledge of the game mechanics, reducing costs and effort in game development while increasing robustness and behavioural variety Christian’s ongoing research stretches beyond video games, investigating the role of computational models of IM for intentional agency, open-ended development and creativity in minimal lifeforms and artificial systems. Christian studied Computer Science, History of Art and Business in Germany and the UK and is now based in London, working towards a PhD in Artificial Intelligence. His work challenges the question how computers could ever become genuinely creative with a highly interdisciplinary approach based on Computing, Cognitive Science and Philosophy. Over the last few years, he published papers on a wide range of topics, held a tutorial on intrinsic motivation in video games, organised workshops on computational serendipity and spent three months at NYU’s Game Innovation Lab for a research collaboration. Christian has substantial industry experience, looking back at three years in the R&D department of SAP SE and a recent internship at Microsoft Research Cambridge. He enjoys working in an international environment with open-minded, passionate people. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Not All the Same: Understanding and Informing Similarity Estimation in Tile-Based Video Games Predicting game difficulty and engagement using AI players Embodiment and computational creativity Intrinsic Motivation in Computational Creativity Applied to Videogames. PhD Thesis. 306 pages. The Relationship of Future State Maximization and von Foerster's Ethical Imperative Through the Lens of Empowerment On the Machine Condition and its Creative Expression. Understanding and Strengthening the Computational Creativity Community: A Report From The Computational Creativity Task Force. Action Selection in the Creative Systems Framework Measuring perceived challenge in digital games: Development & validation of the challenge originating from recent gameplay interaction scale (CORGIS) Generative design in Minecraft: Chronicle challenge Towards Mode Balancing of Generative Models via Diversity Weights Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities Themes Game AI - Previous Next

< Back Prof. Nick Pears University of York Supervisor Nick Pears is a Professor of Computer Vision in York’s Vision, Graphics and Learning (VGL) research group. He works on statistical modelling of 3D shapes, with an emphasis on the human face and head. The Liverpool-York Head Model and the associated Headspace training set has been downloaded by over 100 research groups internationally, with the Universal Head Model being downloaded by 50 research groups. His most recent work with his PhD students has focused on semantic disentanglement of 3D images and how to make autonomous vehicles safer and more trustworthy when using computer vision systems. He is assessor for many PhDs including construction of generative models for novel video content using adversarial deep learning techniques. Email nick.pears@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game AI - Previous Next

< Back Guilherme Matos de Faria University of York iGGi Alum I am a Portuguese student with a background in Artificial Intelligence. In 2016 I started attending video game tournaments and learned to analyse my matches and improve from it. When I did my masters in AI, I noticed that I could join my professional skills and my hobbies together to create something relevant to AI and competitive gaming. A description of James' research: I am looking to better understand which actions and decisions have the biggest impact on the outcome of a game. Currently, I am particularly focused on competitive turn based card games. What are the best players doing to win? How can players adapt to improve their chances of success? These are the questions I am hoping to help answer, giving players a better understanding of the game and how to improve. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

< Back Igor Dall'Avanzi Goldsmiths iGGi Alum Creation of accessible tools for the use of procedural audio in video games The aim of this research is to investigate and provide new tools to developers for the use of procedural audio into video games. Procedural approaches could address different issues that commonly afflict game audio. In music, generative systems are not only less repetitive, but offer more adaptability as well. For what concerns sound design, they can provide not only variety, but stronger and more realistic support to the interaction with the game world; interaction that is becoming even deeper with the advent of VR Yet, these methods still need improvement on different sides. One is the level of quality that procedural audio needs to achieve to compete with the current aesthetic established by the use of rendered sounds and music in the media. Another is the additional amount of work required by the CPU to render the assets on runtime, and its variable cost). Finally, there is a general lack of user-friendly tools, to link common programming languages for audio to game engines. Software like MaxMsp, Pure Data or SuperCollider is used to design generative audio systems. A more accessible integration of these software could promote generative approaches among sound designers and composers in the field, that today have instead access to tools mainly designed to be used with rendered assets. My plan is to bring on research first by focusing on how a higher degree of quality could be addressed, exploring tools like the above mentioned MaxMsp, Pure Data, low level solutions, and machine learning algorithms. Primary research will be run to confront procedurally generated audio content with rendered one; to understand its impact on the player, and the level of quality needed to deliver a satisfactory experience. The creation of more accessible interfaces and tools dedicated to implement procedural audio in video games will be investigated and undertaken. I like to make noises of all sort and to play with them. For this reason I graduated in Music Production in 2016 and, at the moment of writing, I am finishing my final project for an MSc in Sound and Music for Interactive Games at Leeds Beckett University. Composer and sound designer, in the last year I have been focusing on audio implementation and programming, and I am currently exploring machine learning approaches for procedural audio. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game Audio Player Research - Previous Next

< Back Dr Jozef Kulik University of York iGGi Alum Jozef’s first study has focused on developing a better understanding of the challenges and barriers to making accessible games. This identified a vast array of personal, organisational, and external factors which contribute to the difficulties that developers experience when seeking to make their games more accessible, and also identifies avenues which might be helpful. One key finding in this research was that one of the biggest challenges that developers experience relates to a lack of lived experience with disability, or knowledge of the player experience with disabilities. My most recent research is focused on how to effectively extract that knowledge from players with disabilities, then insert it into a large studio within the UK. This research takes a multi-pronged approach to assisting developers in making more accessible games. First by directly assisting a studio with knowledge about their games, second generating potentially transferable knowledge on accessibility issues and player experience for the rest of the industry, and exploring how research methods such as diary study methodology can be valuable in extracting data from natural play environments with people with disabilities. Email joe.kulik@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Paul Cairns Dr Jen Beeston Featured Publication(s): Understanding how we make accessible games: Perspectives from the games industry and players with disabilities A Qualitative Investigation of Real World Accessible Design Experiences within a Large Scale Commercial Game Development Studio Grounded theory of accessible game development What makes icons appealing? The role of processing fluency in predicting icon appeal in different task contexts Themes Accessibility Player Research - Previous Next