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{Multi-Agent Deep Reinforcement Learning for Autonomous Energy Coordination in Demand Response Methods for Residential Distribution Networks
DownloadFall 2023
In the field of collaborative learning and decision-making, this thesis aims to explore the effects of individual and joint rewards on the performance and coordination of agents in complex environments. The research objectives encompass two main aspects: firstly, to determine the objective...
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Data-Driven and Artificial Intelligence Approach to Dynamic Truck Fleet Dispatching and Shovel Allocation Planning in Open-Pit Mines
DownloadFall 2023
An open-pit mine is a highly dynamic environment where different equipment resources are allocated to mining areas to extract metal-bearing rock and waste, for pit development, following a set flow of activities. The material mined is then transported through the mine road network to different...
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Development of AI-based ergonomics risk assessment tools for harmonization of industrial work systems
DownloadFall 2023
Manufacturing industry workers face significant ergonomic risks due to poorly designed work systems. Consequently, it is crucial to periodically assess work systems to identify areas for improvement. However, the assessment process is often disregarded due to the absence of userfriendly...
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Fall 2023
Many works of art are created through the process of an artist sketching and then incrementally increasing the fidelity of the artwork. This requires significant amounts of work and effort throughout, but not all steps require the same amount of artistic input. Certain parts only require...
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Fall 2023
Krishna Guruvayur Sasikumar, Aakash
The application of reinforcement learning (RL) to the optimal control of building systems has gained traction in recent years as it can reduce building energy consumption and improve human comfort, without requiring the knowledge of the building model. However, existing RL solutions for building...
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Fall 2023
The increasing popularity of Deep Neural Networks (DNN) has led to their application to many domains, including Music Generation. However, these large DNN-based models are heavily dependent on their training dataset, which means they perform poorly on musical genres that are out-of-distribution...
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Spring 2023
With machine learning models becoming more complicated and more widely applied to solve real-world challenges, there comes the need to explain their reasoning. In parallel with the advancements of deep learning methods, Explainable AI (XAI) algorithms have been proposed to address the issue of...
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Motion Planning of Robotic Systems in Diagnostic and Therapy Applications Using Control and AI
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This thesis presents significant research on robotic motion planning within diagnostic and therapy applications, with a primary focus on the integration of control and AI techniques. The research encompasses three main contributions: a robotic ultrasound imaging method, a robot-assisted...
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Spring 2023
There has been a renewed interest in commonsense as a stepping stone toward achieving human-level intelligence. By digesting enormous amounts of data in different forms, such as visual, lingual, and sensory, humans are able to create a world model for themselves. It is hypothesized that this...
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Application of Artificial Intelligence in Hip Ultrasound and its Performance in Detecting Developmental Dysplasia of the Hip
DownloadSpring 2022
Developmental Dysplasia of Hip (DDH) which represents a wide range of abnormalities from acetabular dysplasia to fixed dislocation, is mainly defined by a loss of conformity between the femoral head and the acetabulum and it can lead to structural instability and osteoarthritis. The diagnosis of...