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Skip to Search Results- 2Abdi Oskouie, Mina
- 2Birkbeck, Neil Aylon Charles
- 2Cai, Zhipeng
- 2Chen, Jiyang
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 83Machine Learning
- 76Reinforcement Learning
- 42Artificial Intelligence
- 37Machine learning
- 24Natural Language Processing
- 23reinforcement learning
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Fall 2024
Video game development is a highly technical practice that traditionally requires programming skills. This serves as a barrier to entry for would-be developers or those hoping to use games as part of their creative expression. While there have been prior game development tools focused on...
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Fall 2024
Most work in online reinforcement learning (RL) tunes hyperparameters in an offline phase without accounting for the said interaction. This empirical methodology is a reasonable approach to assess how well algorithms can perform but is limited when evaluating algorithms for practical deployment...
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Action Selection for Hammer Shots in Curling: Optimization of Non-convex Continuous Actions With Stochastic Action Outcomes
DownloadSpring 2017
Optimal decision making in the face of uncertainty is an active area of research in artificial intelligence. In this thesis, I present the sport of curling as a novel application domain for research in optimal decision making. I focus on one aspect of the sport, the hammer shot, the last shot...
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Spring 2021
Active sensors, such as active cameras and ultrasound transducers, are becoming more popular. One particular type of active camera, the Pan-Tilt-Zoom (PTZ) camera, has become ubiquitous in surveillance platforms. Given their active nature, active cameras are omnipresent in robotic systems as...
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Fall 2019
Q-learning can be difficult to use in continuous action spaces, because a difficult optimization has to be solved to find the maximal action. Some common strategies have been to discretize the action space, solve the maximization with a powerful optimizer at each step, restrict the functional...