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

< Back Perceptions of Telepresence Robot Form Link Author(s) AI Nordin, M Hudson, A Denisova, J Beeston Abstract More info TBA Link

< Back Towards Mode Balancing of Generative Models via Diversity Weights Link Author(s) S Berns, S Colton, C Guckelsberger Abstract More info TBA Link

< Back Dr James Goodman Queen Mary University of London iGGi Alum James has picked up degrees in Chemistry, History, Mathematics, Business Administration and Machine Learning. After a career in Consultancy and IT Project Management he is now finally doing the research he always wanted to. James is interested in opponent modelling, theory of mind and strategic communication in multi-player games, and how statistical forward planning can be used in modern tabletop board-games (or other turn-based environments). With a constrained budget, how much time should an agent spend thinking about it's own plan versus thinking about what other players might be doing to get in the way. How does this balance vary across different games? His secondary research interests are in using AI-playtesting as a tool for game-balancing and game-design. james.goodman@qmul.ac.uk Email Mastodon https://www.tabletopgames.ai/ Other links Website https://www.linkedin.com/in/james-goodman-b388791/ LinkedIn BlueSky Github Supervisors: Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): Seeding for Success: Skill and Stochasticity in Tabletop Games From Code to Play: Benchmarking Program Search for Games Using Large Language Models Skill Depth in Tabletop Board Games Measuring Randomness in Tabletop Games A case study in AI-assisted board game design Following the leader in multiplayer tabletop games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games MultiTree MCTS in Tabletop Games Visualizing Multiplayer Game Spaces TAG: Terraforming Mars Fingerprinting tabletop games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games AI and Wargaming Metagame Autobalancing for Competitive Multiplayer Games Does it matter how well I know what you’re thinking? Opponent Modelling in an RTS game Weighting NTBEA for game AI optimisation Re-determinizing MCTS in Hanabi Noise reduction and targeted exploration in imitation learning for abstract meaning representation parsing UCL+ Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound Themes Design & Development Game AI - Previous Next

< Back Coupled Kuramoto oscillator-based control laws for both formation and obstacle avoidance control of two-wheeled mobile robots Link Author(s) K Denamganai, T Nakamura, N Hara, K Konishi 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 Light field completion using focal stack propagation Link Author(s) T Broad, M Grierson Abstract More info TBA Link

< Back Quality Evolvability ES: Evolving Individuals With a Distribution of Well Performing and Diverse Offspring Link Author(s) A Katona, DW Franks, JA Walker 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. Roli

< Back MEG adaptation resolves the spatiotemporal characteristics of face-sensitive brain responses Link Author(s) MIG Simpson, SR Johnson, G Prendergast, AV Kokkinakis, E Johnson, ... Abstract More info TBA Link

< Back A Manifesto for More Productive Psychological Games Research Link Author(s) N Ballou Abstract More info TBA Link

< Back Not Very Effective: Validity Issues of the Effectance in Games Scale Link Author(s) N Ballou, H Breitsohl, D Kao, K Gerling, S Deterding Abstract More info TBA Link