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Automated Coordination of Distributed Energy Resources using Local Energy Markets and Reinforcement Learning
DownloadFall 2024
The conventional unidirectional model of the electricity grid operations is no longer sufficient. The continued proliferation of distributed energy resources and the resultant surge in net load variability at the grid edge necessitates deploying adequate demand response methods. This thesis...
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Fall 2016
Current medical imaging professional training uses an apprenticeship model with students following an established doctor and viewing their cases, in what is called a practicum. This posses an issue as students are limited to the cases available during their practicum. To resolve this automated...
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Spring 2024
Recent advances in reinforcement learning (RL) and Human-in-the-Loop (HitL) learning have made human-AI collaboration easier for humans to team with AI agents. Leveraging human expertise and experience with AI agents in intelligent systems can be efficient and beneficial. Still, it is unclear to...
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Fall 2023
Recurrent Neural Networks (RNNs) are typically used to learn representations in partially observable environments. Unfortunately, training RNNs is known to be difficult, and the difficulty increases for agents who learn online and continually interact with the environment. Two common strategies...