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Skip to Search Results- 19Planning
- 11Heuristic Search
- 7Artificial Intelligence
- 6Abstractions
- 6Reinforcement Learning
- 3Machine Learning
- 1Abdullah
- 1Asadi Atui, Kavosh
- 1Barriga Richards, Nicolas A
- 1Brown, Jennifer A.
- 1Faid, Julian TW
- 1Fan, Gaojian
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Fall 2009
For zero-sum games, we have efficient solution techniques. Unfortunately, there are interesting games that are too large to solve. Here, a popular approach is to solve an abstract game that models the original game. We assume that more accurate the abstract games result in stronger strategies....
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Spring 2011
In this thesis, we study theoretically and empirically the additive abstraction-based heuristics. First we present formal general definitions for abstractions that extend to general additive abstractions. We show that the general definition makes proofs of admissibility, consistency, and...
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Fall 2022
In this thesis, we investigate the empirical performance of several experience replay techniques. Efficient experience replay plays an important role in model-free reinforcement learning by improving sample efficiency through reusing past experience. However, replay-based methods were largely...
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Fall 2014
An agent in an adversarial, imperfect information environment must sometimes decide whether or not to take an action and, if they take the action, must choose a parameter value associated with that action. Examples include choosing to buy or sell some amount of resources or choosing whether or...
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Fall 2010
We investigate the use of machine learning to create effective heuristics for single-agent search. Our method aims to generate a sequence of heuristics from a given weak heuristic h{0} and a set of unlabeled training instances using a bootstrapping procedure. The training instances that can be...
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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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Fall 2014
Heuristic search has been shown to be an effective way to solve state-space problems. While many heuristic search techniques are guaranteed to find the best solution, these are often not feasible given practical resource requirements. In such cases, it is necessary to sacrifice solution...
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Enhancements to Methods for Planning and Scheduling Fabrication Projects Utilizing Multiskilled Labour Resources
DownloadSpring 2023
In prefabrication and off-site construction, various multiskilled work crews need to be assembled to work on different workstations to process custom-designed work units, each having specific requirements for material handling, assembly connections, welding, etc. However, the frequent labour...
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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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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...