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- 11Abstractions
- 6Artificial Intelligence
- 4Planning
- 3Heuristic search
- 3Machine Learning
- 18Graduate and Postdoctoral Studies (GPS), Faculty of
- 18Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 4Computing Science, Department of
- 4Computing Science, Department of/Technical Reports (Computing Science)
- 2Art and Design, Department of
- 2Art and Design, Department of/Master's Theses (Art & Design)
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Fall 2021
Traffic congestion is a severe problem in many cities. One way to reduce it is by optimizing traffic signal timings. Experts spend a lot of time analyzing traffic patterns to produce good handcrafted timing schedules. However, these timing schedules can be less responsive when there is a sudden...
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Solving Witness-type Triangle Puzzles Faster with an Automatically Learned Human-Explainable Predicate
DownloadFall 2023
The Witness is a game with difficult combinatorial puzzles that are challenging for both human players and artificial intelligence based solvers. Indeed, the number of candidate solution paths to the largest puzzle considered in this thesis is on the order of 10^(15) and search-based solvers can...
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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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Spring 2016
Game theoretic solution concepts, such as Nash equilibrium strategies that are optimal against worst case opponents, provide guidance in finding desirable autonomous agent behaviour. In particular, we wish to approximate solutions to complex, dynamic tasks, such as negotiation or bidding in...