Search Results

< Back Automatic Generation of Text for Match Recaps using Esport Caster Commentaries Link Author(s) O Olarewaju, AV Kokkinakis, S Demediuk, J Roberstson, I Nölle, S Patra, D Slawson, AP Chitayat, A Coates, B Kirman, A Drachen, M Ursu, F Block, J Hook Abstract More info TBA Link

< Back Metrics of games-with-a-purpose for NLP applications Link Author(s) J Chamberlain, R Bartle, U Kruschwitz, C Madge, M Poesio Abstract More info TBA Link

< Back Towards an Ontology of Wargame Design Link Author(s) L Ouriques, CE Barbosa, J Kritz, G Xexéo Abstract More info TBA Link

< Back Rolling horizon evolutionary algorithms for general video game playing Link Author(s) RD Gaina, S Devlin, SM Lucas, D Perez-Liebana Abstract More info TBA Link

< Back Machine Learning with Applications Link Author(s) Charles Ringer, Sondess Missaoui, Victoria J Hodge, Alan Pedrassoli Chitayat, Athanasios Kokkinakis, Sagarika Patra, Simon Demediuk, Alvaro Caceres Munoz, Oluseji Olarewaju, Marian Ursu, Ben Kirman, Jonathan Hook, Florian Block, Anders Drachen, James Alfred Walker Abstract More info TBA Link

< Back Measuring game experience using visual distractors Link Author(s) J Cutting Abstract More info TBA Link

< Back “That Darned Sandstorm”: A Study of Procedural Generation through Archaeological Storytelling Link Author(s) F Smith Nicholls, M Cook Abstract More info TBA Link

< Back Alex Flint University of York iGGi PG Researcher Available for placement Alex has an academic background in Psychology and Human-Computer Interaction. Their Master’s dissertation comparing measures of perceived challenge and demand in video games was published at CHI 2023. Alex has previously worked on the Research Operations team at PlaytestCloud and as a freelance Games User Researcher. They are also a Student Video Games Ambassador for UKIE, and regularly volunteer at conferences such as CHI Play and the GamesUR Summit. When they aren’t at their desk, you can find Alex figure skating, playing roller derby, or DJing 80’s rock. Alex’s research focuses on levelling up the narrative testing practices of indie video game developers. Narrative testing is a specialised games user research (GUR) practice that requires resources and knowledge not easily accessible to indie developers, meaning they are often disadvantaged compared to their larger AAA counterparts. Thus, Alex's work proposes the direct study of indie developers to level the playing field by democratising narrative testing best practices and empowering non-research team members to conduct GUR activities. Alex aims to achieve this goal by: 1) Defining narrative testing best practices. 2) Identifying key challenges indie developers face when evaluating narrative. 3) Co-designing and evaluating narrative testing prototype(s). 4) Assessing methods for disseminating GUR knowledge. The successful completion of this work will impact how indie studios conduct narrative testing, ultimately leading to the creation of better games. alex.flint@york.ac.uk Email Mastodon https://alexflint.tech Other links Website https://www.linkedin.com/in/alexlflint/ LinkedIn https://bsky.app/profile/alexlflint.bsky.social BlueSky Github Supervisor: Dr Alena Denisova Dr Jon Hook Featured Publication(s): Comparing Measures of perceived challenge and demand in video games: Exploring the conceptual dimensions of CORGIS and VGDS Faking handedness: Individual differences in ability to fake handedness, social cognitions of the handedness of others, and a forensic application using Bayes’ theorem Themes Design & Development Player Research - Previous Next

iGGi PhD Projects - listing iGGi PhD Projects 2023 Game AI 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 Game AI Automatic Evaluation of Tabletop Games This project proposal aims to research and develop methods to accurately evaluate the impact of modern Tabletop Games components in different aspects of gameplay. Price Game AI Duration Diego Pérez-Liébana Read More Game AI Principled and Scalable Exploration Techniques for Reinforcement Learning In this project, you will develop principled and scalable exploration techniques based on reducing model uncertainty. Price Game AI Duration Paulo Rauber Read More Game AI Evolving Perception for Game Agents This project will investigate game agents in open world games which evolve their senses and world representation alongside learning what actions to take in each state. We will evolve game agents with highly alien behaviours which nevertheless have high fitness in the open world environment, while investigating important scientific questions about how senses and world representations evolved in humans. Price Game AI Duration Alex Wade, Peter Cowling Read More Load More

< Back Defining the esports bettor: evidence from an online panel survey of emerging adults Link Author(s) H Wardle, E Petrovskaya, D Zendle Abstract More info TBA Link

< Back Portfolio search and optimization for general strategy game-playing Link Author(s) A Dockhorn, J Hurtado-Grueso, D Jeurissen, L Xu, D Perez-Liebana Abstract More info TBA Link

< Back Dr William Smith University of York Supervisor William Smith is a Reader in the Computer Vision and Pattern Recognition research group in the Department of Computer Science at the University of York. He is currently a Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow and an Associate Editor of the journal Pattern Recognition. His research interests span vision, graphics and ML. Specifically, physics-based and 3D computer vision, shape and appearance modelling and the application of statistics and machine learning to these areas. The application areas in which he most commonly works are face/body analysis and synthesis, surveying and mapping, object capture and inverse rendering. A wide variety of tools and areas of maths are often useful in his research such as: convex optimisation, nonlinear optimisation, manifold learning, learning/optimisation on manifolds, computational geometry and low level computer vision (e.g. features and correspondence). He leads a team of five PhD students and one postdoc and has published over 100 papers, many in the top conferences and journals in the field. He was General Chair for the ACM SIGGRAPH European Conference on Visual Media Production in 2019 and is Program Chair for the British Machine Vision Conference in 2020. Research themes: Game AI Game Design Computational Creativity Graphics and rendering Content creation william.smith@york.ac.uk Email Mastodon https://www-users.cs.york.ac.uk/wsmith/ Other links Website https://www.linkedin.com/in/william-smith-b5421a70/ LinkedIn BlueSky https://github.com/waps101 Github Themes Creative Computing Design & Development Game AI Player Research - Previous Next