< Back Learning to see Link Author(s) M Akten Abstract More info TBA Link

< Back iGGi conference 2021 Mark the date for our next IGGI Conference: 08 - 09 September 2021 PhD students discuss and showcase their research into new technologies and directions for games.Come along and find out about new ideas, meet future employees, and steer the direction of research in the world’s largest games PhD programme. Click for Tickets and more info here - coming soon Previous 8 Jul 2021 Next

< Back Towards Mode Balancing of Generative Models via Diversity Weights Link Author(s) S Berns, S Colton, C Guckelsberger 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. Georgia Institute of Technology

< 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 Affective Uplift During Video Game Play: A Naturalistic Case Study Link Author(s) M Vuorre, N Ballou, T Hakman, K Magnusson, AK Przybylski Abstract More info TBA Link

< Back Expressivity of Parameterized and Data-driven Representations in Quality Diversity Search Link Author(s) A Hagg, S Berns, A Asteroth, S Colton, T Bäck 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 Gamifying language resource acquisition Link Author(s) CJ Madge Abstract More info TBA Link

< Back GRACER: Improving the Accuracy of RACER Classifier Using A Greedy Approach Link Author(s) P Hosseini, A Basiri Abstract More info TBA Link

< Back A Vocabulary of Board Game Dynamics Link Author(s) J Kritz, G Xexéo Abstract More info TBA Link

< Back General video game ai: A multitrack framework for evaluating agents, games, and content generation algorithms Link Author(s) D Perez-Liebana, J Liu, A Khalifa, RD Gaina, J Togelius, SM Lucas Abstract More info TBA Link