Search
Skip to Search Results- 90Artificial Intelligence
- 27Machine Learning
- 14Computing Science
- 12Reinforcement Learning
- 8Deep Learning
- 8Planning
- 4Müller, Martin
- 3Mueller, Martin
- 3Schaeffer, Jonathan
- 2Dr. Carrie Demmans Epp
- 2Johanson, Michael
- 2Lin, Guohui
- 54Graduate and Postdoctoral Studies (GPS), Faculty of
- 54Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 19Computing Science, Department of
- 18Computing Science, Department of/Technical Reports (Computing Science)
- 8WISEST Summer Research Program
- 8WISEST Summer Research Program/WISEST Research Posters
-
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...
-
Automated Coordination of Distributed Energy Resources using Local Energy Markets and Reinforcement Learning
DownloadFall 2024
The conventional unidirectional model of the electricity grid operations is no longer sufficient. The continued proliferation of distributed energy resources and the resultant surge in net load variability at the grid edge necessitates deploying adequate demand response methods. This thesis...
-
Fall 2012
Automated sports commentary is a form of automated narrative and human-computer interaction. Sports commentary exists to keep the viewer informed and entertained. One way to entertain the viewer is by telling brief stories relevant to the game in progress. We introduce a system called the...
-
2013
Valenzano, Richard, Müller, Martin, Xie, Fan
Most of the satisficing planners which are based on heuristic search iteratively improve their solution quality through an anytime approach. Typically, the lowest-cost solution found so far is used to constrain the search. This avoids areas of the state space which cannot directly lead to lower...
-
2023-10-13
The slides accompany a ChatGPT workshop that is intended for university students to learn more about generative AI and in the context of ChatGPT. This work is licensed under a Creative Commons license so that others may share and adapt the content for other purposes as long as appropriate credit...
-
Fall 2024
The success of deep learning is partly due to the sheer size of modern models. However, such large models strain the capabilities of mobile or resourceconstrained devices. Ergo, reducing the resource demands of AI models is essential before AI can be deployed on such devices. One promising...
-
Fall 2009
Answer typing is an important aspect of the question answering process. Most commonly addressed with the use of a fixed set of possible answer classes via question classification, answer typing influences which answers will ultimately be selected as correct. Answer typing introduces the concept...
-
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...
-
Spring 2023
There has been a renewed interest in commonsense as a stepping stone toward achieving human-level intelligence. By digesting enormous amounts of data in different forms, such as visual, lingual, and sensory, humans are able to create a world model for themselves. It is hypothesized that this...
-
Spring 2016
Algorithmic decipherment is a prime example of a truly unsupervised problem. This thesis presents several algorithms developed for the purpose of decrypting unknown alphabetic scripts representing unknown languages. We assume that symbols in scripts which contain no more than a few dozen unique...