Martin Balla is currently a PhD student in the Game AI group at Queen Mary University of London as part of the Intelligent Games and Game Intelligence Doctoral Training (IGGI) programme. He is researching ways to improve the generalisation capabilities of Reinforcement Learning agents in video games and simulated environments. His main line of research is around Goal Conditioned and Hierarchical Reinforcement Learning. Prior to starting his PhD he studied Computer Science at the University of Essex.

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Universal Value Function Approximator

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