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Spring 2010
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...
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Spring 2010
The Monte-Carlo Tree Search (MCTS) algorithm Upper Confidence bounds applied to Trees (UCT) has become extremely popular in computer games research. Because of the importance of this family of algorithms, a deeper understanding of when and how their different enhancements work is desirable. To...
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Spring 2015
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...