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Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 91Reinforcement Learning
- 21Machine Learning
- 10Artificial Intelligence
- 6Transfer Learning
- 5Planning
- 5Representation Learning
- 1Abbasi Brujeni, Lena
- 1Abbasi-Yadkori, Yasin
- 1Aghakasiri, Kiarash
- 1Alikhasi, Mahdi
- 1Asadi Atui, Kavosh
- 1Banafsheh Rafiee
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Decision Frequency Adaptation in Reinforcement Learning Using Continuous Options with Open-Loop Policies
DownloadFall 2023
In classic reinforcement learning(RL) for continuous control, agents make decisions at discrete and fixed time intervals. The duration between decisions becomes a crucial hyperparameter. Setting it too short may increase the problem’s difficulty by requiring the agent to make numerous decisions...
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Design and Optimal Operation of a Virtual Power Plant with Bidirectional Electric Vehicle Chargers
DownloadSpring 2023
Virtual power plants (VPPs) can enhance reliability and efficiency of power systems with a high share of renewables. However, their adoption largely depends on their profitability, which is difficult to maximize due to the heterogeneity of their components, different sources of uncertainty and...
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Spring 2024
Alarm floods present substantial challenges to industrial process safety, given their diverse causes and potential for severe consequences. Modern process industries involve sophisticated networks of devices that are interconnected in both upstream and downstream directions. The...
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Spring 2010
In this thesis, a Reinforcement Learning (RL) method called Sarsa is used to dynamically tune a PI-controller for a Continuous Stirred Tank Heater (CSTH) experimental setup. The proposed approach uses an approximate model to train the RL agent in the simulation environment before implementation...
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Spring 2023
Vision is one of the essential means for humans to perceive the world. Similarly, today's intelligent robot agents rely on camera images to perform complex tasks in the real world. Due to the ever-changing nature of the real world, intelligent robot agents must continually learn from...
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Spring 2019
In the reinforcement learning (RL) problem an agent must learn how to act optimally through trial-and-error interactions with a complex, unknown, stochastic environment. The actions taken by the agent influence not just the immediate reward it observes but also the future states and rewards it...
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Fall 2024
This thesis studies a virtual power plant (VPP) that trades the bidirectional charging flexibility of privately owned plug-in electric vehicles (EVs) in a real-time electricity market to maximize its profit. The main contribution of this thesis is the development of scalable and efficient...
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Spring 2011
Off-policy reinforcement learning is useful in many contexts. Maei, Sutton, Szepesvari, and others, have recently introduced a new class of algorithms, the most advanced of which is GQ(lambda), for off-policy reinforcement learning. These algorithms are the first stable methods for general...
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Fall 2022
OpenSpiel is an open-source software system for implementing high-performance software players for many different computer games. Hex is a two-player game of perfect information used in a variety of computer games research projects. The OpenSpiel project has implemented a version of the AlphaZero...
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Feature Generalization in Deep Reinforcement Learning: An Investigation into Representation Properties
DownloadFall 2022
In this thesis, we investigate the connection between the properties and the generalization performance of representations learned by deep reinforcement learning algorithms. Much of the earlier work on representation learning for reinforcement learning focused on designing fixed-basis...