< Back Genetic optimisation of BCI systems for identifying games related cognitive states Link Author(s) A Iacob, M Morosan, F Sepulveda, R Poli Abstract More info TBA Link

< Back European Strategy on AI: Are we truly fostering social good? Link Author(s) F Foffano, T Scantamburlo, A Cortés, C Bissolo Abstract More info TBA Link

< Back NEST 2.18. 0 Link Author(s) J Jordan, R Deepu, J Mitchell, JM Eppler, S Spreizer, J Hahne, S Berns, ... Abstract More info TBA Link

< Back Multimodal Generation of Contextualized Jokes for a Real-Time Virtual Character Link Author(s) T Kiderle, CG Dobre, J Nasir, C Gonzalez Diaz, H Ritschel, S Klein, ... Abstract More info TBA Link

< Back Dr Ivan Bravi Queen Mary University of London iGGi Alum Ivan Bravi has obtained his B.Sc and M.Sc in Engineering of Computer Systems at the Politecnico di Milano, Italy. From January to July 2016 he was Visiting Scholar at the NYU’s Game Innovation Lab in New York, under the supervision of Prof. Julian Togelius. Since October 2017 he's an IGGI PhD student at Queen Mary University of London under the supervision of Simon Lucas. Ivan has published several workshop and conference papers in different venues such as IJCAI, Evostar, CIG, FDG, AAAI and CoG. Automatic playtesting of games can significantly streamline the process of designing, developing and releasing a game. It is also a possible application of Artificial General Intelligence (AGI): having a set of flexible algorithms that can play games regardless of their type decouples the two problems (playtesting and developing AGI algorithms) advancing both independently. When it comes to developing new AGI algorithms for game-playing a crucial characteristic is the ability of expressing different behaviours. Most of the research has focused on peak performance game-playing agents, this research project instead focuses on producing agents that are able to show different playing styles (behaviours) with no explicit domain information embedded in the algorithm. Behavioural expressivity arises from the parameterisable components of an algorithm. In classical Statistical Forward Planning (SFP) it is very straightforward to adjust these, e.g. how far ahead it's planning. A very important component of SFP algorithms is the heuristic function used to evaluate the quality of game states. Being able to define heuristics in a game-agnostic manner is a key element in maintaining the algorithms generally. Email i.bravi@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): Program Committee and Subreviewers Evaluating and Enhancing Gameplay Behavioural Expressivity of Planning-Playing Artificial Intelligence for Automatic Playtesting Self-adaptive MCTS for General Video Game Playing Rinascimento: Playing Splendor-Like Games With Event-Value Functions Rinascimento: searching the behaviour space of Splendor Rinascimento: using event-value functions for playing Splendor Learning local forward models on unforgiving games Rinascimento: Optimising statistical forward planning agents for playing splendor A local approach to forward model learning: Results on the game of life game Game AI hyperparameter tuning in rinascimento Efficient evolutionary methods for game agent optimisation: Model-based is best Shallow decision-making analysis in general video game playing Evolving UCT alternatives for general video game playing Evolving game-specific UCB alternatives for general video game playing Themes Game AI 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 Time to die: Death prediction in dota 2 using deep learning Link Author(s) A Katona, R Spick, VJ Hodge, S Demediuk, F Block, A Drachen, ... Abstract More info TBA Link

< Back Investigating sensorimotor contingencies in the enactive interface Link Author(s) JK Gibbs, K Devlin Abstract More info TBA Link

< Back Tired and Wired: Sleep Deprivation Prevents Affective Renormalisation During Exposure to Ambiguous Threat Link Author(s) E Sullivan, C McCall, M Croissant, LM Henderson, G Schofield, S Cairney Abstract More info TBA Link

< Back Dr Sarah West University of York Supervisor Sarah West is an interdisciplinary researcher and practitioner working to bring diverse voices into research through participatory approaches, including citizen science. Sarah is currently Director of SEI York, a Centre of the Stockholm Environment Institute, a science-to-policy research institute, whose York Centre is at the University of York in the Department of Environment and Geography. She has used citizen science approaches to address topics as diverse as air pollution, biodiversity, parenting, and exploring community responses to Covid-19. Her projects mainly take place in the UK and Kenya. Sarah has spent over a decade designing, running and evaluating citizen science projects, and together with other SEI colleagues has written reports for Defra, UK Earth Observation Framework and journal articles exploring who participates in citizen science, their motivations for participation, and how volunteers can be recruited and retained. She is particularly interested in exploring how different messaging and communication affects participation in citizen science projects. Email sarah.west@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Accessibility Design & Development Player Research - Previous Next

< Back Sunny Thaicharoen Queen Mary University of London iGGi PG Researcher Sunny is a passionate esports enthusiast, with a love of MOBA games. His background is in engineering and entrepreneurship, with a Master of Technology Entrepreneurship degree from University College London. He is the creator of YGOscope, a statistical game data platform for a competitive card game, Yu-Gi-Oh. Sunny is an avid player of competitive Dota in his spare time, and is also a keen theme park enthusiast. He is interested in modelling metagames of MOBAs through game data and player research, particularly how players adopt the most effective strategies when changes to the stable gameplay state occurs. A description of Sunny's research: The project focuses on how the META - most effective tactics available - of MOBA games shift during disruption (usually through gameplay updates) between states of ignorance and stability within the player space of these games, to deepen our understanding of how players adapt to the changes that these gameplay updates cause, and why. There is a large degree of variability of how new METAs develops, and currently there is little research on the meta and metagame front. Available research so far has been based on defining the phenomena and resulting effects of gameplay updates, but little modelling has been done to attempt bring these fragmented pieces of knowledge together and attempt to structure them. The study and structuring of this phenomena can be an ideal starting point in understanding how effective strategies develop not only in MOBAs or video games, but any other competitive games such as chess, trading card games or sports. Email t.thaicharoen@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Anders Drachen Dr Jeremy Gow Featured Publication(s): An ecosystem framework for the meta in esport games Themes Esports Game Data Player Research - Previous Next

< Back How To Save A World: The Go-Along Interview as Game Preservation Methodology in Wurm Online Link Author(s) F Smith Nicholls, M Cook Abstract More info TBA Link