About
The Game AI research Group at Queen Mary University of London, led by Prof Simon M. Lucas, was created on 1st August 2017.
Our research involves using games as a test-bed for and an application of advanced artificial intelligence (AI) methods. Games provide an ideal way to study all aspects of AI, but within our group we place particular emphasis on general AI: the challenge is to develop software agents that can rapidly learn to play any games to a high standard just by playing them. Much of this study is done within the framework of General Video Game AI (http://gvgai.net).
Within our group we study two main approaches to general game AI: deep learning, and deep statistical search using a forward model (including Monte Carlo Tree Search and Rolling Horizon Evolution).
The research has creative applications, and we study the use of AI to help automate the game design process. We measure the performance and experience of AI agents playing games to assess their quality and tune their design. For this purpose, the deep statistical search methods are especially interesting as they are often able to play novel games to a reasonable standard without any training, producing high performance within milliseconds of being presented with a new game variant.
We also research games with a purpose, and serious game applications.
Our group is closely associated with the EPSRC funded IGGI Centre for Doctoral Training (http://iggi.org.uk), and we currently have openings for PhD students via the IGGI programme and also through other sources of funding (self-funded students are also welcome to apply).
Contact
- GitHub：GAIGResearch
- Twitter: GameAI_QMUL
- YouTube: Game AI Group at QMUL