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Skip to Search Results- 50Artificial Intelligence
- 27Machine Learning
- 27Natural Language Processing
- 11Reinforcement Learning
- 8Deep Learning
- 5Computer Vision
- 1Akbari, Mojtaba
- 1Alexander, Graham
- 1Asadi Atui, Kavosh
- 1Ashley, Dylan R
- 1Ashrafi Asli, Seyed Arad
- 1Atrazhev, Peter
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Fall 2009
Answer typing is an important aspect of the question answering process. Most commonly addressed with the use of a fixed set of possible answer classes via question classification, answer typing influences which answers will ultimately be selected as correct. Answer typing introduces the concept...
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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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Fall 2011
Pinball is fast-paced arcade-style game of which the origins date back hundreds of years. Game playing robots exist for billiards, foosball, and soccer and each have their own unique challenges. The speed that balls move in pinball machines requires that players have quick reactions. We created...
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Fall 2012
Automated sports commentary is a form of automated narrative and human-computer interaction. Sports commentary exists to keep the viewer informed and entertained. One way to entertain the viewer is by telling brief stories relevant to the game in progress. We introduce a system called the...
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Fall 2012
Functional Magnetic Resonance Imaging (fMRI) measures the dynamic activity of each voxel of a brain. This dissertation addresses the challenge of learning a diagnostic classifier that uses a subject’s fMRI data to distinguish subjects with neuropsychiatric disorders from healthy controls. fMRI...
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Fall 2013
Many important problems can be cast as state-space problems. In this dissertation we study a general paradigm for solving state-space problems which we name Cluster-and-Conquer (C&C). Algorithms that follow the C&C paradigm use the concept of equivalent states to reduce the number of states...
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Fall 2013
Given nothing but the generative model of the environment, Monte Carlo Tree Search techniques have recently shown spectacular results on domains previously thought to be intractable. In this thesis we try to develop generic techniques for temporal abstraction inside MCTS that would allow the...
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Fall 2014
Designing competitive Artificial Intelligence (AI) systems for Real-Time Strategy (RTS) games often requires a large amount of expert knowledge (resulting in hard-coded rules for the AI system to follow). However, aspects of an RTS agent can be learned from human replay data. In this thesis, we...
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Fall 2014
An agent in an adversarial, imperfect information environment must sometimes decide whether or not to take an action and, if they take the action, must choose a parameter value associated with that action. Examples include choosing to buy or sell some amount of resources or choosing whether or...