Game Design (Postgraduate)
The module examines the nature of fun and engagement in the context of game design, and includes the study of how to integrate narrative into gameplay and how to criticise game design. The module also covers how to design and deploy objective measures of player experience and how to apply these to analyse game logs in a number of case studies. The effects of game AI on player experience are also considered. The module also aims to include guest lectures from designers and developers of published games and / or academic game AI researchers.
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The main focus of my research is AI and Games ? both using games an ideal test-bed for AI research, and in using AI to make better game-playing agents, generating new games and optimising game content and game parameters. This leads on to studying various types of machine learning, with particular emphasis on reinforcement learning and evolutionary algorithms.
I am the director of the Game AI Research Group at Queen Mary University of London and am also the Queen Mary lead for the EPSRC funded Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI).
Research includes novel approaches to General Video Game AI.
Games are a natural source of noisy optimisation algorithms, and in our group we have developed an efficient approach to this that combines evolutionary algorithms with combinatorial bandit algorithms. It is called the N-Tuple Bandit Evolutionary Algorithm and will soon be made open-source: more details available on request.