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Skip to Search Results- 19Planning
- 5Reinforcement Learning
- 4Heuristic Search
- 3Artificial Intelligence
- 2Scheduling
- 1Abstraction
- 1Asadi Atui, Kavosh
- 1Brown, Jennifer A.
- 1Faid, Julian TW
- 1Fan, Gaojian
- 1Jabbari Arfaee, Shahab
- 1Kumar,Chandan
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Spring 2014
Retail areas within cities have traditionally not only satisfied the demands for various goods and services, but also promoted community sustainability and healthy lifestyles. Since the end of World War II (WWII), retail innovations have occurred rapidly and unexpectedly. In retail development,...
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Fall 2018
Canada has the third largest oil reserves in the world where 97% of these reserves are located in the oil sands, Alberta province. The product resulted from the extraction of oil sands reserves is called bitumen which can be diluted and shipped to the market or it can be proceeded and upgraded...
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Fall 2013
Scaffolds are temporary structures that are built to support workers and materials and facilitate direct work on construction sites. A considerable amount of man power resources are consumed by industrial construction scaffolding, which makes effective planning and estimation of the same very...
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Fall 2013
Many important problems can be cast as state-space problems. In this dissertation we study a general paradigm for solving state-space problems which we name Cluster-and-Conquer (C&C). Algorithms that follow the C&C paradigm use the concept of equivalent states to reduce the number of states...
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Spring 2016
This thesis proposes, analyzes and tests different exploration-based techniques in Greedy Best-First Search (GBFS) for satisficing planning. First, we show the potential of exploration-based techniques by combining GBFS and random walk exploration locally. We then conduct deep analysis on how...
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Strengths, Weaknesses, and Combinations of Model-based and Model-free Reinforcement Learning
DownloadSpring 2016
Reinforcement learning algorithms are conventionally divided into two approaches: a model-based approach that builds a model of the environment and then computes a value function from the model, and a model-free approach that directly estimates the value function. The first contribution of this...
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Planning for the Future of Urban Mobility: Interviews with Planning Professionals in Five Major Canadian Cities
DownloadFall 2020
Given that our urban centres have been dominated by the private car for a hundred years, this thesis asked what is next for Canadian cities. Previous research on the future of urban mobility, and specifically city planning and autonomous vehicles, has been from an American or Australian context....
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Social Actor Engagement in Municipal Decision-Making for Parks, Planning, and Civil Society in Edmonton, Alberta, Canada 1960-2010: Institutional Intersections
DownloadSpring 2020
Edmonton, Alberta, has a unique approach to public spaces that sees conjoined creation and development sharing of public spaces for the collective benefit of the community and stakeholders; this approach began 100 years ago. Green or open spaces, natural areas, the river valley, City of Edmonton...
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Fall 2019
In this thesis, we study merge-and-shrink (M&S), a flexible abstraction technique for generating heuristics for cost optimal planning. We first propose three novel merging strategies for M&S, namely, Undirected Min-Cut (UMC), Maximum Intermediate Abstraction Size Minimizing (MIASM), and Dynamic...
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Fall 2022
This thesis investigates a new approach to model-based reinforcement learning using background planning: mixing (approximate) dynamic programming updates and model-free updates, similar to the Dyna architecture. Background planning with learned models is often worse than model-free alternatives,...