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< Back Different rules for binocular combination of luminance flicker in cortical and subcortical pathways Link Author(s) FG Segala, A Bruno, MT Aung, AR Wade, DH Baker Abstract More info TBA Link

< Back Comparative evaluation in the wild: Systems for the expressive rendering of music Link Author(s) K Worrall, Z Yin, T Collins 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. Human VR

< Back Dr Thryn Henderson University of York iGGi Alum Thryn’s phd explored the practices of personal vignette games, with a particular interest in the vignette game’s approaches to digital persona, their roots in approachable DIY culture, and their importance to marginalised creators. Publications from their work can be found in the Digra 2020 archive and Persona Studies Volume 6, Issue 2 . Thryn’s interest in gaming grows from a delight in telling stories. They endeavour to find the spaces where play incorporates and encourages collaborative narrative, poetry, theatre, activism, subversion, surprise and expression. Most of Thryn’s work in playful media can be found in zines, cardboard installations, paper games, hidden screens, or roaming through the woods around the UK. They are a co-founder of the playful design co-operative Furtive Shambles, currently producing experimental live and tabletop game experiences. thrynhenderson@gmail.com Email Mastodon https://furtiveshambles.com Other links Website LinkedIn BlueSky Github Themes Design & Development - Previous Next

< Back Predicting skill learning in a large, longitudinal MOBA dataset Link Author(s) M Aung, V Bonometti, A Drachen, P Cowling, AV Kokkinakis, C Yoder, ... Abstract More info TBA Link

< Back Trace it like you believe it: Time-continuous believability prediction Link Author(s) C Pacheco, D Melhart, A Liapis, GN Yannakakis, D Perez-Liebana Abstract More info TBA Link

< Back Lon-ea at SemEval-2023 Task 11: A Comparison of Activation Functions for Soft and Hard Label Prediction Link Author(s) P Hosseini, M Hosseini, SS Al-Azzawi, M Liwicki, I Castro, M Purver Abstract More info TBA Link

< Back Deep unsupervised multi-view detection of video game stream highlights Link Author(s) C Ringer, MA Nicolaou Abstract More info TBA Link

< Back Prof. Simon Lucas Queen Mary University of London iGGi Co-Investigator Supervisor Simon Lucas is a professor of Artificial Intelligence and Head of the School of Electronic Engineering and Computer Science at Queen Mary University of London where he also heads the Game AI Research Group. He holds a PhD degree (1991) in Electronics and Computer Science from the University of Southampton. He is the founding Editor-in-Chief of the IEEE Transactions on Games and co-founded the IEEE Conference on Games. His research involves developing and applying computational intelligence techniques to build better game AI, use AI to design better games, provide deep insights into the nature of intelligence and work towards Artificial General Intelligence. He is the QMUL lead for the EPSRC-funded CDT in Intelligent Games and Game Intelligence (IGGI). He has supervised more that 15 PhD students to completion, most of them in Game AI. Research themes: Game AI Agents (RL, Monte Carlo Tree Search, Rolling Horizon Evolution) Learning Forward Models Automated Game Design, Procedural Content Generation Game AI for real-world problem solving simon.lucas@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/profiles/lucassimon.html Other links Website LinkedIn BlueSky https://github.com/simon-lucas Github Themes Game AI - Previous Next

< Back Dominik Jeurissen Queen Mary University of London iGGi PG Researcher Hey, I'm Dominik Jeurissen, and I'm passionate about both software engineering and machine learning, with a particular interest in fully autonomous agents that do not rely on absurd amounts of data. My focus areas include reinforcement learning, unsupervised learning, and the emerging capabilities of large language models. I earned my MSc in Artificial Intelligence from Maastricht University and my BSc in Computer Science with a focus on Applied Mathematics from RWTH Aachen. During my undergraduate studies, I worked as a software engineer at INFORM GmbH, contributing to their supply management software, add*ONE. A description of Dominik's research: My PhD is a collaboration with Creative Assembly , focusing on researching AI for complex strategy games, such as Total War. With the recent emergence of Large Language Models (LLMs), I’m exploring their potential to enhance game-playing agents. LLMs can instantly recall knowledge on almost any topic (though not without occasional errors), perform basic reasoning, and are easily configured for a wide range of text-based tasks. These abilities make them especially promising for game development, where machine learning agents often struggle due to constantly changing game environments. d.jeurissen@qmul.ac.uk Email https://commandercero.github.io/ Mastodon Other links Website https://www.linkedin.com/in/dominik-jeurissen/ LinkedIn https://bsky.app/profile/dominikjeurissen.bsky.social BlueSky https://github.com/CommanderCero Github Supervisors: Dr Diego Pérez-Liébana Dr Jeremy Gow Featured Publication(s): Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Generating Diverse and Competitive Play-Styles for Strategy Games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Automatic Goal Discovery in Subgoal Monte Carlo Tree Search Game state and action abstracting monte carlo tree search for general strategy game-playing Portfolio search and optimization for general strategy game-playing The Design Of" Stratega": A General Strategy Games Framework Themes Design & Development Game AI Game Data - Previous Next

< Back Pilar Zhang Qiu Queen Mary University of London iGGi Alum Pilar is a researcher with a background in Design Engineering. She has a keen interest in user experience and interaction, wearables and the use of cyber-physical systems in the medical field. Her PhD centres around the creation of play assessments for neuromotor conditions in children with cerebral palsy. This gravitates around the idea that better and more objective clinical data can be obtained through gamification of common assessments. Please note: Updating of profile text in progress Email Mastodon https://www.pilarzhangqiu.com/ Other links Website https://www.linkedin.com/in/pilar-zhang-qiu/ LinkedIn BlueSky https://github.com/pili-zhangqiu Github Themes Applied Games - Previous Next

< Back Interactive machine learning for more expressive game interactions Link Author(s) C Gonzalez Diaz, P Perry, R Fiebrink Abstract More info TBA Link