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Skip to Search Results- 2Abdi Oskouie, Mina
- 2Birkbeck, Neil Aylon Charles
- 2Cai, Zhipeng
- 2Chen, Jiyang
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 74Machine Learning
- 70Reinforcement Learning
- 41Artificial Intelligence
- 36Machine learning
- 22Natural Language Processing
- 22Reinforcement learning
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Fall 2016
Real-time strategy (RTS) video games are known for being one of the most complex and strategic games for humans to play. With a unique combination of strategic thinking and dexterous mouse movements, RTS games make for a very intense and exciting game-play experience. In recent years the games AI...
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High performance live migration over low-bandwidth, high-delay network with loss prevention
DownloadFall 2010
Virtualization technology has attracted considerable interest. It allows several virtual machines to run concurrently inside a physical host, which brings multiple advantages. One of the most useful features is called live migration, during which a virtual machine can be migrated over network...
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High-dimensional data mining: subspace clustering, outlier detection and applications to classification
DownloadSpring 2010
Data mining in high dimensionality almost inevitably faces the consequences of increasing sparsity and declining differentiation between points. This is problematic because we usually exploit these differences for approaches such as clustering and outlier detection. In addition, the exponentially...
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Highway Lane change under uncertainty with Deep Reinforcement Learning based motion planner
DownloadSpring 2020
Motion Planning is a fundamental component of a mobile robot to reach its goal safely avoiding collision. For a self-driving car on a highway, the presence of non-communicating vehicles, specially those whose intent is unknown, creates a lot of uncertainty for the motion planner in generating a...
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Hindsight Rational Learning for Sequential Decision-Making: Foundations and Experimental Applications
DownloadFall 2022
This thesis develops foundations for the development of dependable, scalable reinforcement learning algorithms with strong connections to game theory. I present a version of rationality for learning---one grounded in the learner's experience and connected with the rationality concepts of...