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< Back Intrinsic elicitation: A model and design approach for games collecting human subject data Link Author(s) D Gundry, S Deterding Abstract More info TBA Link

< Back Mapping Farmed Landscapes from Remote Sensing Link Author(s) M Conserva, A Wilson, C Stanton, V Batchu, V Gulshan Abstract More info TBA Link

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

< Back General video game artificial intelligence Link Author(s) DP Liebana, SM Lucas, RD Gaina, J Togelius, A Khalifa, J Liu Abstract More info TBA Link

< Back Dr Dino Ratcliffe Queen Mary University of London iGGi Alum Teaching AI agents transferable skills for game playing My research focuses on the ability of an AI agent to be able to evaluate the various skills it would need to master a game, such as in an FPS (first person shooter) like doom. If the agent can learn to cluster actions that may split into strategies such as attacking enemies, gathering ammo/health and avoiding enemy fire this information could then be used in similar games. This information would also provide a base for being to evaluate players on a skill level, giving a much more granular view of their strengths and weaknesses in any of these games. This could then be used for better matchmaking in team games, placing players into teams whose skill sets complement each other. Other applications include being able to guide the player into situations that give them more experience in the areas they are weakest. Dino started a MSci in computer science at the University of Essex in 2011. During the next 4 years, he focused on modules that involved improving technical skills and Artificial Intelligence. He was the winner of the K.F Bowden Memorial prize in two separate years. Dino worked at the London startup Signal Media during the summer of 2014 and continued to work for them part time during my masters year. He graduated with a 1st class degree. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Cross-lingual style transfer with conditional prior VAE and style loss Author's declaration Win or learn fast proximal policy optimisation Domain Adaptation for Deep Reinforcement Learning in Visually Distinct Games Clyde: A deep reinforcement learning doom playing agent Themes Game AI - Previous Next

< Back Navigating the Lines: Towards a Multi-Perspective Approach on Videogame Monetisation Link Author(s) P Declerck, B Dupont, E Grosemans, E Petrovskaya, M Geudens, M Sas, ... Abstract More info TBA Link

Novel video narrative from recorded content Theme Creative Computing Project proposed & supervised by Nick Pears To discuss whether this project could become your PhD proposal please email: nick.pears@york.ac.uk < Back Novel video narrative from recorded content Project proposal abstract: In order to stimulate interest and engagement in games, it is important to give players a wide variety of video content that can provide scenario variations each time they engage with the game. However, creating a large volume of diverse video content manually is expensive and time consuming. This project aims to generate novel video narratives from recorded content with minimal human intervention. This requires automatic visual scene understanding that generates auto tagging of scene content and scene actions, either on a frame-by-frame or short clip basis. As well as understanding frame content, action segmentation strategies will be developed and evaluated. This will enable construction of short novel video narratives - for example, from a manually-defined storyline. Deep learning tools and techniques will be employed throughout this project. Supervisor: Nick Pears Based at:

< Back Casual Creators in the Wild: A Typology of Commercial Generative Creativity Support Tools Link Author(s) E Petrovskaya, CS Deterding, S Colton Abstract More info TBA Link

< Back Dr Memo Akten Goldsmiths iGGi Alum Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression. This research investigates how the latest developments in Deep Learning can be used to create intelligent systems that enhance artistic expression. These are systems that learn – both offline and online – and people interact with and gesturally ‘conduct’ to expressively produce and manipulate text, images and sounds. The desired relationship between human and machine is analogous to that between an Art Director and graphic designer, or film director and video editor – i.e. a visionary communicates their vision to a ‘doer’ who produces the output under the direction of the visionary, shaping the output with their own vision and skills. Crucially, the desired human-machine relationship here also draws inspirations from that between a pianist and piano, or a conductor and orchestra – i.e. again a visionary communicates their vision to a system which produces the output, but this communication is real-time, continuous and expressive; it’s an immediate response to everything that has been produced so far, creating a closed feedback loop. The key area that the research tackles is as follows: Given a large corpus (e.g. thousands or millions) of example data, we can train a generative deep model. That model will hopefully contain some kind of ‘knowledge’ about the data and its underlying structure. The questions are: i) How can we investigate what the model has learnt? ii) how can we do this interactively and in real-time, and expressively explore the knowledge that the model contains iii) how can we use this to steer the model to produce not just anything that resembles the training data, but what *we* want it to produce, *when* we want it to produce it, again in real-time and through expressive, continuous interaction and control. Memo Akten is an artist and researcher from Istanbul, Turkey. His work explores the collisions between nature, science, technology, ethics, ritual, tradition and religion. He studies and works with complex systems, behaviour, algorithms and software; and collaborates across many disciplines spanning video, sound, light, dance, software, online works, installations and performances. Akten received the Prix Ars Electronica Golden Nica in 2013 for his collaboration with Quayola, ‘Forms’. Exhibitions and performances include the Grand Palais, Paris; Victoria & Albert Museum, London; Royal Opera House, London; Garage Center for Contemporary Culture, Moscow; La Gaîté lyrique, Paris; Holon Design Museum, Israel and the EYE Film Institute, Amsterdam. Please note: Updating of profile text in progress Email memo@memo.tv Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Top-Rated LABS Abstracts 2021 Deep visual instruments: realtime continuous, meaningful human control over deep neural networks for creative expression Deep Meditations: Controlled navigation of latent space Learning to see: you are what you see Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks Mixed-initiative creative interfaces Learning to see Real-time interactive sequence generation and control with Recurrent Neural Network ensembles Collaborative creativity with Monte-Carlo Tree Search and Convolutional Neural Networks Sequence generation with a physiologically plausible model of handwriting and Recurrent Mixture Density Networks Deepdream is blowing my mind All watched over by machines of loving grace: Deepdream edition Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks Themes Game AI - Previous Next

< Back The State of the Art in Procedural Audio Link Author(s) D Menexopoulos, P Pestana, J Reiss Abstract More info TBA Link

< Back Dr Tara Collingwoode-Williams Goldsmiths iGGi Alum Tara is an IGGI PhD student from Goldsmiths University taking her Mphil/PhD in Intelligent Games/Game intelligence with a focus on Avatar Embodiment and Interaction within Virtual Reality. Before this she graduated with a Bsc in Creative Computing. Over the years, her interdisciplinary profile has enabled her to work as a Technical Support and Researcher with many organisations in relation to her research, such as UCL, Great Ormond Street Hospital, George Mason Serious Games Institute in the United States where she also co-lectured a XR Games Module and, more recently as an Associate Lecturer in Goldsmiths University teaching Unity based XR experience development. Currently, she is contracting for USTech as an Assistant UX researcher at Facebook whilst completing her PhD program. With this rise in demand for Head Mounted Displays (HMDs), so is the need to create Embodied Shared Virtual Environments (ESVE) where users may experience authentic social interactions. Tara’s research presents an exploratory examination of Embodiment - meaning the subjective feeling of owning a virtual representation in VR, and specifically Consistency in Embodiment - relating to how we prioritize and syncronise objective attributes of embodiment (i.e avatar representation) in order to create ESVEs which supports more intuitive social interaction. The goal is to understand how different technical setups could have a psychological impact on participants' experiences in ESVE. This research hopes to inform development of successful social interaction in a variety of applications in VR, ranging from training to gaming. Tara presently holds a position as Lekturer in VR at Goldsmiths, Universtiy of London. Email tc.williams@gold.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): The Psychological Impact of the Configuration of Self-Representation in Immersive Virtual Reality Delivering Bad News: VR Embodiment of Self Evaluation in Medical Communication Training The impact of self-representation and consistency in collaborative virtual environments G487 (P) Is clinician gaze and body language associated with their ability to identify safeguarding cues? Evaluating virtual reality experiences through participant choices A discussion of the use of virtual reality for training healthcare practitioners to recognize child protection issues A study of professional awareness using immersive virtual reality: the responses of general practitioners to child safeguarding concerns The effect of lip and arm synchronization on embodiment: a pilot study Themes Applied Games Player Research - Previous Next

< Back Not All the Same: Understanding and Informing Similarity Estimation in Tile-Based Video Games Link Author(s) S Berns, V Volz, L Tokarchuk, S Snodgrass, C Guckelsberger Abstract More info TBA Link