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< Back Metagame Autobalancing for Competitive Multiplayer Games Link Author(s) D Hernandez, CTT Gbadamosi, J Goodman, JA Walker Abstract More info TBA Link

< Back The need for the human-centred explanation for ML-based clinical decision support systems Link Author(s) Y Jia, JA McDermid, N Hughes, MA Sujan, T Lawton, I Habli Abstract More info TBA Link

< Back The @artbhot Text-To-Image Twitter Bot. Link Author(s) A Smith, S Colton Abstract More info TBA Link

< Back Better Dead than a Damsel: Gender Representation and Player Churn Link Author(s) Lauren Winter, Sarah Masters Abstract More info TBA Link

< Back Evaluating virtual reality experiences through participant choices Link Author(s) M Murcia-López, T Collingwoode-Williams, W Steptoe, R Schwartz, ... 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. Forma

< Back “Slow down and look”: Desirable aspects of failure in video games, from the perspective of players. Link Author(s) C Foch, B Kirman Abstract More info TBA Link

< Back From Theory to Behaviour: Towards a General Model of Engagement Link Author(s) V Bonometti, C Ringer, M Ruiz, A Wade, A Drachen Abstract More info TBA Link

< Back Dr Adrian Bors University of York Supervisor Adrian G. Bors is an Associate Professor at the University of York and has published more than 150 papers in international journals and conferences in the areas of his research interests. He is interested in supervising projects related to the application of novel artificial intelligence methods and computer vision in Game AI. One of the areas of interest is in the modelling of game characters (intelligent agent) continuously learning from their environments, able to transfer their knowledge from one stage to the next, while accumulating the information, like human/animal beings and enabling to continuously adapt to their environments. Another topic of interest is represented by conditional image and video generation for developing game environments. The conditional video/image generation will depend on certain factors that can be pre-established or be the result of self-learning by an (intelligent agent). Most existing games relying on no movement representation lack in representing realistic and continuous movement. In this direction of research, we will aim to generated video which would be consistent with realistic movement of game characters. Specific attention will be paid to modelling the interaction of the generated movement with the environment or other actors (game characters). In another direction of research, Adrian G. Bors will supervise projects in digital watermarking of 3D graphical characters. Codes will be invisible embedded and retrieved from the 3D graphics representations. The code embedded, like the DNA in human/animals, will enable the character to act in specific ways, defining behavioural traits in similarly looking graphics characters. adrian.bors@york.ac.uk Email https://www.researchgate.net/profile/Adrian-Bors Mastodon https://www-users.cs.york.ac.uk/adrian/ Other links Website https://www.linkedin.com/in/adrian-bors-32a3668/ LinkedIn BlueSky https://github.com/AdrianBors Github Themes Game AI - 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 Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): 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 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 Bodystorming in SocialVR to Support Collaborative Embodied Ideation Link Author(s) C Gonzalez Diaz, R Fiebrink, P Perry, R Gibson, B Martelli, S Deterding, ... Abstract More info TBA Link