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- 5Machine learning
- 3Artificial Intelligence
- 2Adaptive switching
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- 1Al-Saffar, Mohammed
- 1Atrazhev, Peter
- 1Bastani, Meysam
- 1Bowling, Michael
- 1Cutumisu, Maria
- 1Dogru, Oguzhan
- 25Graduate and Postdoctoral Studies (GPS), Faculty of
- 25Graduate and Postdoctoral Studies (GPS), Faculty of /Theses and Dissertations
- 3Computing Science, Department of
- 3Computing Science, Department of/Technical Reports (Computing Science)
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- 1Electrical and Computer Engineering, Department of/Journal Articles (Electrical and Computer Engineering)
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Reinforcement Learning based Distributed BESS Management for Mitigating Overvoltage Issues in Systems with High PV Penetration
Download2020-01-01
Al-Saffar, Mohammed, Musilek, Petr
High levels of penetration of distributed photovoltaic generators can cause serious overvoltage issues, especially during periods of high power generation and light loads. There have been many solutions proposed to mitigate the voltage problems, some of them using battery energy storage systems...
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Spring 2022
The repetitiveness and precision of manufacturing tasks has increased the need for robots in the automation of the manufacturing industry; however, the complex and varied nature of manufacturing production lines poses challenges in terms of applying the rule-based automation approach. This has...
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Spring 2023
Process industries involve processes that have complex, interdependent, and sometimes uncontrollable/unobservable features that are subject to a variety of uncertainties such as operational fluctuations, sensory noises, process anomalies, human involvement, market volatility, and so forth. In the...
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2007
Wang, Tao, Schuurmans, Dale, Bowling, Michael, Lizotte, Daniel
Technical report TR07-05. We investigate novel, dual algorithms for dynamic programming and reinforcement learning, based on maintaining explicit representations of stationary distributions instead of value functions. In particular, we investigate the convergence properties of standard dynamic...
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Spring 2012
We study linear estimation based on perturbed data when performance is measured by a matrix norm of the expected residual error, in particular, the case in which there are many unknowns, but the “best” estimator is sparse, or has small L1-norm. We propose a Lasso-like procedure that finds the...
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Fall 2017
The idea of an amputee playing the piano with all the flair and grace of an able-handed person may seem like a futuristic fantasy. While many prosthetic limbs look lifelike, finding one that also moves naturally has proved more of a challenge for both researchers and amputees. Even though...
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Fall 2015
The control of powered prosthetic arms has been researched for over 50 years, yet prosthetic control remains an open problem, not just from a research perspective, but from a clinical perspective as well. Significant advances have been made in the manufacture of highly functional prosthetic...
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Spring 2022
Sajjadi Ghaemmaghami, Saeedehsadat
Today’s users are spending more time on web applications. Many users browse web applications and navigate through different web pages. They may have different interests, especially when it comes to large-scale applications. The more the developers of the applications know about their users’ needs...
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Fall 2009
Character behaviours in computer role-playing games have a significant impact on game-play, but are often difficult for story authors to implement and modify. Many computer games use custom scripts to control the behaviours of non-player characters (NPCs). Therefore, a story author must write...
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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...