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- The impact of self-representation and consistency in collaborative virtual environments
< Back The impact of self-representation and consistency in collaborative virtual environments Link Author(s) T Collingwoode-Williams, Z O'Shea, M Gillies, X Pan Abstract More info TBA Link
- Graz University of Technology
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. Graz University of Technology
- Modelling the interactions in metaverse videogames | iGGi PhD
Modelling the interactions in metaverse videogames Theme Player Research Project proposed & supervised by Ignacio Castro To discuss whether this project could become your PhD proposal please email: i.castro@qmul.ac.uk < Back Modelling the interactions in metaverse videogames Project proposal abstract: What is the role of AR and VR technologies in the interactions of participants? Do they foment or reduce social interactions and if so what type of interactions? This project will seek to inform AR and VR enabled videogames by analysing existing online platforms supporting these technologies. The project will collect comprehensive datasets from existing online metaverse platforms and analyse them using a variety of tools and techniques from social network analysis, natural language processing and economics. The findings will then be fed and compared with those from existing AR/VR videogames. Supervisor: Ignacio Castro Based at:
- Pinpointing the problem: Providing page numbers for citations as a crucial part of open science
< Back Pinpointing the problem: Providing page numbers for citations as a crucial part of open science Link Author(s) LY Xiao, N Ballou Abstract More info TBA Link
- Frontiers of GVGAI Planning
< Back Frontiers of GVGAI Planning Link Author(s) DP Liebana, RD Gaina Abstract More info TBA Link
- Generating calligraphic trajectories with model predictive control
< Back Generating calligraphic trajectories with model predictive control Link Author(s) D Berio, S Calinon, FF Leymarie Abstract More info TBA Link
- Exploring the multiverse of analysis options for the Addiction Stroop
< Back Exploring the multiverse of analysis options for the Addiction Stroop Link Author(s) A Jones, T Stafford, E Petrovskaya Abstract More info TBA Link
- Measuring perceived challenge in digital games: Development & validation of the challenge originating from recent gameplay interaction scale (CORGIS)
< Back Measuring perceived challenge in digital games: Development & validation of the challenge originating from recent gameplay interaction scale (CORGIS) Link Author(s) A Denisova, P Cairns, C Guckelsberger, D Zendle Abstract More info TBA Link
- Automatic Goal Discovery in Subgoal Monte Carlo Tree Search
< Back Automatic Goal Discovery in Subgoal Monte Carlo Tree Search Link Author(s) D Jeurissen, MHM Winands, CF Sironi, D Perez-Liebana Abstract More info TBA Link
- University of Waterloo (Canada)
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. University of Waterloo (Canada)
- ESL UK
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. ESL UK
- The Multi-Agent Reinforcement Learning in Malm\" O (MARL\" O) Competition
< Back The Multi-Agent Reinforcement Learning in Malm\" O (MARL\" O) Competition Link Author(s) Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, Andre Kramer, Sam Devlin, Raluca D Gaina, Daniel Ionita Abstract More info TBA Link





