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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 Dr Daniel Berio Goldsmiths iGGi Alum AutoGraff: A Procedural Model of Graffiti Form. (Industry placement at Media Molecule) The purpose of this study is to investigate techniques for the procedural and interactive generation of synthetic instances of graffiti art. Considering graffiti as a special case of the calligraphic tradition, I propose a "movement centric" alternative to traditional curve generation techniques, in which a curve is defined through a physiologically plausible simulation of a (human) movement underlying its production rather than by an explicit definition of its geometry. In my thesis, I consider both single traces left by a brush (in a series of strokes) and the extension to 2D shapes (representing deformed letters in a large variety of artistic styles). I demonstrate how this approach is useful in a number of settings including computer aided design (CAD), procedural content generation for virtual environments in games and movies, computer animation as well as for the smooth control of robotic drawing devices. Daniel Berio is a researcher and artist from Florence, Italy. Since a young age Daniel was actively involved in the international graffiti art scene. In parallel he developed a professional career initially as a graphic designer and later as a graphics programmer in video games, multimedia and audio-visual software. In 2013 he obtained a Master degree from the Royal Academy of Art in The Hague (Netherlands), where he developed drawing machines and installations materializing graffiti-inspired procedural forms. Today Daniel is continuing his research in the procedural generation of graffiti within the IGGI (Intelligent Games and Game Intelligence) PhD program at Goldsmiths, University of London. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Word-as-image for semantic typography Optimality Principles in the Procedural Generation of Graffiti Style SURFACE: Xbox Controlled Hot-wire Foam Cutter The role of image characteristics and embodiment in the evaluation of graffiti Emergence in the Expressive Machine The CyberAnthill: A Computational Sculpture Sketch-Based Modeling of Parametric Shapes Artistic Sketching for Expressive Coding Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks Sequence generation with a physiologically plausible model of handwriting and Recurrent Mixture Density Networks AutoGraff: Towards a computational understanding of graffiti writing and related art forms Kinematics reconstruction of static calligraphic traces from curvilinear shape features Interactive generation of calligraphic trajectories from Gaussian mixtures Sketching and Layering Graffiti Primitives. Kinematic Reconstruction of Calligraphic Traces from Shape Features Expressive curve editing with the sigma lognormal model Dynamic graffiti stylisation with stochastic optimal control Computer aided design of handwriting trajectories with the kinematic theory of rapid human movements Generating calligraphic trajectories with model predictive control Learning dynamic graffiti strokes with a compliant robot Computational models for the analysis and synthesis of graffiti tag strokes Towards human-robot gesture recognition using point-based medialness Transhuman Expression Human-Machine Interaction as a Neutral Base for a New Artistic and Creative Practice Themes Game AI - Previous Next

< Back Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks Link Author(s) M Akten Abstract More info TBA Link

< Back Stylegan2 distillation for feed-forward image manipulation Link Author(s) Y Viazovetskyi, V Ivashkin, E Kashin Abstract More info TBA Link

< Back From Passive Viewer to Active Fan: Towards the Design and Large-Scale Evaluation of Interactive Audience Experiences in Esports and Beyond Link Author(s) Alan Pedrassoli Chitayat, Alistair Coates, Florian Block, Anders Drachen, James Alfred Walker, James Dean, Mark McConachie, Peter York Abstract More info TBA Link

< Back An ecosystem framework for the meta in esport games Link Author(s) S Thaicharoen, J Gow, A Drachen Abstract More info TBA Link

< Back From Code to Play: Benchmarking Program Search for Games Using Large Language Models Link Author(s) M Eberhardinger, J Goodman, A Dockhorn, D Perez-Liebana, RD Gaina, ... Abstract More info TBA Link

< Back Dr Adrián Barahona-Ríos University of York iGGi Alum From 2018 and in collaboration with Sony Interactive Entertainment Europe, Adrián is researching strategies to increase the efficiency in the creation of procedural audio models for video games by using DSP and machine learning approaches. His main research interests, applied to the synthesis of sound effects, are generative deep learning (GANs, RNNs and VAEs) to synthesise raw audio and machine learning to find out the best parameters for a synthesiser to generate a target sound. Adrián has been enthusiastic about sound and more specifically about game audio since he began his studies. By the time he completed an HND in Creative Media Production in Madrid, he started working in the industry as a recording engineer in an ADR studio for the Spanish localisation of video games (such as Fallout 4, Until Dawn or Just Cause 3). He moved from Spain to the UK in 2015 to take a BA (top-up) in Music Production at the Southampton Solent University and an MSc in Sound Design at the University of Edinburgh immediately after. During that journey, he focused his career in procedural audio and explored ways to create models for interactive applications by using different techniques. Email adrian.barahona.rios@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor Dr Tom Collins Featured Publication(s): RESP: Reference-guided Sequential Prompting for Visual Glitch Detection in Video Games Deep Learning for the Synthesis of Sound Effects NoiseBandNet: controllable time-varying neural synthesis of sound effects using filterbanks Sonifying energy consumption using SpecSinGAN SpecSinGAN: Sound Effect Variation Synthesis Using Single-Image GANs Synthesising Knocking Sound Effects Using Conditional WaveGAN Perception of emotions in knocking sounds: An evaluation study Perceptual Evaluation of Modal Synthesis for Impact-Based Sounds Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Themes Creative Computing Game Audio - Previous Next

< Back Dr Fiona McNab University of York Supervisor During a postdoc at the Karolinksa Institute in Stockholm, Fiona investigated working memory and attention, providing empirical support for a role for the basal ganglia in the control of access to working memory and identification of changes in the dopamine system related to working memory training. At The Wellcome Trust Centre for Neuroimaging, UCL, with a Wellcome Trust Career Development Fellowship, she designed the working memory game in the large-scale smartphone study; “The Great Brain Experiment ”, leading to studies of different types of distraction in younger adults as well as in healthy ageing. In 2013 she moved to Birmingham University, where she conducted fMRI and behavioural studies of attention and working memory, and behavioural studies of the effects of competition on working memory. Fiona is now a lecturer in the Department of Psychology at the University of York. She is using fMRI and behavioural studies to investigate what limits working memory, how different types of distractors are successfully ignored and how working memory changes through development, with healthy aging, as well as in certain patient groups. Part of her work uses data from a new set of working memory games, which are currently available to play (York Memory Games, YORMEGA ). She is particularly interested in supervising students on the following topics: Understanding the limitations of working memory and the role of attention using games Understanding age-related changes in cognition using games, Cognitive training using games. Research themes: Game Design Games with a Purpose Player Experience Gamification Games for Cognition Research Games for Cognitive Training Email fiona.mcnab@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games - Previous Next

< Back Transhuman Expression Human-Machine Interaction as a Neutral Base for a New Artistic and Creative Practice Link Author(s) D Berio, P Cruz, J Echevarria Abstract More info TBA Link

< Back Automating game-design and game-agent balancing through computational intelligence Link Author(s) M Morosan Abstract More info TBA Link

< Back How Could They Win? An Exploration of Win Condition for Esports Narratives Link Author(s) AP Chitayat, FO Block, JA Walker, A Drachen Abstract More info TBA Link