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Integral Urbanism: Investigating the Materiality and Spatiality of the University of Alberta Quadrangle
DownloadFall 2015
The university quadrangle is a space that exists on the majority of North American campuses, yet detailed investigation into the creation, existence and perpetuation of the quadrangle has been minimal. Considering how universities look to distinguish themselves from one another in search of the...
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Interrelating Prediction and Control Objectives in Episodic Actor-Critic Reinforcement Learning
DownloadFall 2020
The reinforcement learning framework provides a simple way to study computational intelligence as the interaction between an agent and an environment. The goal of an agent is to accrue as much reward as possible by intelligently choosing actions given states. This problem of finding a policy that...
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Spring 2010
The Monte-Carlo Tree Search (MCTS) algorithm Upper Confidence bounds applied to Trees (UCT) has become extremely popular in computer games research. Because of the importance of this family of algorithms, a deeper understanding of when and how their different enhancements work is desirable. To...
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Fall 2015
Artificial Intelligence (AI) techniques have been widely used in video games to control non-playable characters. More recently, AI has been applied to automated story generation with the objective of managing the player’s experience in an interactive narrative. Such AI experience managers can...
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Spring 2014
Coach learning is a key component for developing quality coaches. While researchers have identified many ways that coaches learn, there is little agreement as to how coaches learn best. As a way of examining these discrepancies found in the research, this study’s aim was to explore how Canadian...
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Fall 2020
Word sense disambiguation (WSD) is one of the core tasks in natural language processing and its objective is to identify the sense of a content word (nouns, verbs, adjectives, and adverbs) in context, given a predefined sense inventory. Although WSD is a monolingual task, it has been conjectured...
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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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Spring 2016
In model-based reinforcement learning a model is learned which is then used to find good actions. What model to learn? We investigate these questions in the context of two different approaches to model-based reinforcement learning. We also investigate how one should learn and plan when the reward...
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Fall 2012
The earthwork operations for reclamation add challenges and complications to common earthworks schedule and aspects such as placement locations and hauling routes…etc. The reclamation earthworks require that the soil layers structure before disturbing the land must remain the same after...
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Motion Planning of Robotic Systems in Diagnostic and Therapy Applications Using Control and AI
DownloadFall 2023
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...