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  • Spring 2010

    Naddaf, Yavar

    This research focuses on developing AI agents that play arbitrary Atari 2600 console games without having any game-specific assumptions or prior knowledge. Two main approaches are considered: reinforcement learning based methods and search based methods. The RL-based methods use feature vectors...

  • Spring 2015

    Sriram, Srinivasan

    In this thesis, I study the problem of Monte-Carlo Planning in deterministic do- mains with sparse rewards. A popular algorithm in this suite, UCT, is studied. A new algorithm to incorporate state generalization in UCT using estimates of sim- ilar nodes and a distance metric is presented. The...

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