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< Back Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data Link ​ Author(s) C Ringer, M Nicolaou, JA Walker Abstract ​ More info TBA ​ Link

< Back Emotional and functional challenge in core and avant-garde games Link ​ Author(s) T Cole, P Cairns, M Gillies Abstract ​ More info TBA ​ Link

< Back Mark the Date! iGGi Con 2024 - 11+12 Sep The iGGi Conference is the annual showcase of our 60+ PhD Researchers, allowing a birds-eye view into their work, and a chance to bring academic research, innovation and the games industry together. Following the success of the conferences in 2022 and 2023, the iGGi Con 2024 will take place at the University of York. More information to follow in a few months. ​ Previous 20 Oct 2023 Next

< Back WARDS: Modelling the Worth of Vision in MOBA's Link ​ Author(s) AP Chitayat, A Kokkinakis, S Patra, S Demediuk, J Robertson, ... Abstract ​ More info TBA ​ Link

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. Fusebox

iGGi PhD Projects 2023 Immersive Technology 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 Immersive Technology ​ Places That Don't Exist The goal of this project is to combine state-of-the-art 3D computer vision and procedural content generation to create game-ready scene models and assets from existing media. Price Immersive Technology Duration William Smith Read More Immersive Technology ​ Tactile Interaction With Virtual Reality Content In this project the student will explore the use of vibrating motors distributed over the human hand (e.g. using a wearable glove) to give tactile feedback about the physical interactions happening in a VR. Price Immersive Technology Duration Lorenzo Jamone & Valkyrie Industries Read More Load More

< Back MAP-Elites to Generate a Team of Agents that Elicits Diverse Automated Gameplay Link ​ Author(s) C Guerrero-Romero, D Perez-Liebana Abstract ​ More info TBA ​ Link

< Back UCL+ Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound Link ​ Author(s) J Goodman, A Vlachos, J Naradowsky Abstract ​ More info TBA ​ Link

< Back Sketch-Based Modeling of Parametric Shapes Link ​ Author(s) D Berio, P Cruz, J Echevarria Abstract ​ More info TBA ​ Link

< Back Social experiences of people with disabilities in playing (in) accessible digital games Link ​ Author(s) J Beeston Abstract ​ More info TBA ​ Link

< Back ​ Dr Martin Balla Queen Mary University of London ​ iGGi Alum ​ Available for post-PhD position 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 https://www.twitter.com/@ballamist Twitter 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

< Back Naive mesh-to-mesh coloured model generation using 3D GANs Link ​ Author(s) R Spick, S Demediuk, J Alfred Walker Abstract ​ More info TBA ​ Link