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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.