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- Training | iGGi PhD
Training 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. Training The training programme is an essential part of the iGGi PhD. It helps students acquire the knowledge and skills they need to do great research -- research that can change both video games and wider society. The programme has a practical focus on the design and development of games. By deepening our PGRs' understanding of games, we aim to motivate and enable PhD research that has real relevance to how games are made and played. Page Index: The Modules - Bringing Researchers Together - Training Requirements The Modules Because iGGi offers a four year PhD programme, the PG Researchers (PGRs) are able to commit substantial time to this training during their first year. There are four modules, with delivery shared by the University of York and Queen Mary University of London: Game Design (York) PGRs learn how to conceive, design, prototype and playtest their own games, be it for entertainment or a 'serious' purpose like health, education, or research. Game Development (QMUL) The module provides hands-on training developing video games using industry-standard game engines. iGGi PGRs work together to prototype a new game in one week . It also introduces a range of state-of-the-art technologies for game development, such as novel interaction techniques, AI opponents and collaborators, and procedural content generation. Methods and Data (York) PGRs learn various methods for empirically studying games and players, including standard HCI methods and data science techniques for gaining insights from large game data sets. Research Impact & Engagement (QMUL) PGRs learn how to engage industry, players, and other societal stakeholders early on in their research, how to conduct responsible research and innovation that is overall beneficial to human wellbeing, and how to present their work online, to the media, and industry. Video Placeholder - to display Game Dev YouTube playlist >> For iGGi news and updates, including event announcements, follow us on social media Bringing Researchers Together A key aim of this training is to bring new researchers together as a well-connected cohort who will carry on learning from, and supporting each other throughout their studies. This has helped us build a strong iGGi community of researchers across four universities and multiple research fields, with a common goal of doing world class PhD research on games. Each module is delivered in two two-week blocks, with the exception of the remotely-supervised individual project. Six weeks of the training takes place in the Autumn of the first year, and another eight weeks is scheduled throughout the rest of first year. For researchers in receipt of an iGGi EPSRC studentship, travel and accommodation is provided for York researchers to study in London, and vice versa. Training Requirements Completing the training programme, including passing the modules, is a compulsory part of the iGGi PhD programme. The Game Development module does assume some knowledge of programming, at least the equivalent of an introductory class.
- System and method for training a machine learning model
< Back System and method for training a machine learning model Link Author(s) R Spick, G Moss, T Bradley, PV Amadori Abstract More info TBA Link
- Lessons from testing an evolutionary automated game balancer in industry
< Back Lessons from testing an evolutionary automated game balancer in industry Link Author(s) M Morosan, R Poli Abstract More info TBA Link
- Frontiers of GVGAI Planning
< Back Frontiers of GVGAI Planning Link Author(s) DP Liebana, RD Gaina Abstract More info TBA Link
- Measuring game experience using visual distractors
< Back Measuring game experience using visual distractors Link Author(s) J Cutting Abstract More info TBA Link
- Bridging Generative Deep Learning and Computational Creativity
< Back Bridging Generative Deep Learning and Computational Creativity Link Author(s) S Berns, S Colton Abstract More info TBA Link
- Using Virtual Reality to Investigate the Influence of Sleep Deprivation on In-the-Moment Arousal During Exposure to Prolonged Threats
< 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
- Playing nethack with llms: Potential & limitations as zero-shot agents
< Back Playing nethack with llms: Potential & limitations as zero-shot agents Link Author(s) D Jeurissen, D Perez-Liebana, J Gow, D Cakmak, J Kwan Abstract More info TBA Link
- Understanding how we make accessible games: Perspectives from the games industry and players with disabilities
< Back Understanding how we make accessible games: Perspectives from the games industry and players with disabilities Link Author(s) J Kulik Abstract More info TBA Link
- Otto-von-Guericke University Magdeburg
iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Otto-von-Guericke University Magdeburg
- Play Style Identification Using Low-Level Representations of Play Traces in MicroRTS
< Back Play Style Identification Using Low-Level Representations of Play Traces in MicroRTS Link Author(s) R Yu Xia, J Gow, S Lucas Abstract More info TBA Link
- Robust Imitation Learning for Automated Game Testing
< Back Robust Imitation Learning for Automated Game Testing Link Author(s) PV Amadori, T Bradley, R Spick, G Moss Abstract More info TBA Link



