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Building Player Profiles in Mobile Monetisation: A Machine Learning Approach Theme Game Data Project proposed & supervised by David Zendle To discuss whether this project could become your PhD proposal please email: david.zendle@york.ac.uk < Back Building Player Profiles in Mobile Monetisation: A Machine Learning Approach Project proposal abstract: This project aims to use machine learning techniques to segment and profile mobile gamers in terms of their in-game spending. Estimates suggest that more than 2.6bn people play mobile games globally; that more than 80 billion mobile games are downloaded annually; and that mobile gaming accounts for almost $100bn in transactions every year. Despite the profitability of mobile gaming, little is known about how different kinds of players spend money in mobile games. Informal theories regarding specific differences in gaming are widely espoused: one influential model, for example, posits the existence of a small but profitable layer of heavily-involved 'whales', and much larger groups of smaller-spending 'dolphins' and 'minnows'. However, it is unclear whether this structure really does explain the monetisation of most games; and whether monetisation may vary between games; and between cultural contexts. In this project, we will take a data-driven approach, and apply a variety of machine learning techniques to large datasets of real player transactions. By both applying and developing algorithmic techniques for the analysis of such data, we will help build an understanding of how in-game spending may be profiled. This project would suit a machine learning specialist; a quantitative social scientist, or a data scientist wishing to do impactful work. It will be supervised by David Zendle, one of the world's leading experts on video game monetisation, and may involve one or more industrial partners who will share player data for the project. Supervisor: David Zendle Based at:

Principled and Scalable Exploration Techniques for Reinforcement Learning Theme Game AI Project proposed & supervised by Paulo Rauber To discuss whether this project could become your PhD proposal please email: p.rauber@qmul.ac.uk < Back Principled and Scalable Exploration Techniques for Reinforcement Learning Project proposal abstract: Reinforcement learning has received significant attention due to its success in training agents that play popular games such as Go , Starcraft II , Dota 2 , and others. Inefficient exploration, one of the earliest problems recognized in the field, still limits the success of reinforcement learning approaches that do not require domain knowledge. Although techniques like posterior sampling convincingly solve hard exploration problems in simple domains ( https://searchworks.stanford.edu/view/11891201 ), scalable exploration techniques remain elusive. In this project, you will develop principled and scalable exploration techniques based on reducing model uncertainty ( https://arxiv.org/abs/1609.04436 ). Besides benefiting from games as excellent testbeds, this project has the potential to radically improve automated playtesting. Supervisor: Paulo Rauber Based at:

< Back Best Game Related Research Award Goes to iGGi Today, iGGi won the Best Game Related Research Award at the Game Republic 20th Anniversary Awards!! The ceremony was part of GaMaYo #21 (by Game Makers Yorkshire and the North ) which took place today, Thursday, 23 November 2023 at Tileyard North in Wakefield, and the award was sponsored by Red Kite Games . For further details please follow this link to the related news item on Game Republic's website. Big thank yous go to the organisers, hosts and sponsor! Last but not least: a WELL DONE to the iGGi Researchers!!! Previous 23 Nov 2023 Next

< Back Intelligent Games and Game Intelligence at Develop:Brighton 12-14 July Want to improve the relationship between your game AI and your players? Or polish your VR character’s social interaction skills? Or discuss the latest academic research in the metaverse? Or just chance a flirt with Amy Smith ’s @artbhot? We are super excited to announce that @iggiphd will be attending @developconf in full force with 3 talks and over 20 researchers. This is our first big event since the pandemic and we are stoked! Who else is coming? We would love to meet you all at our stand! Click here for more information. Previous 2 Jul 2022 Next