Search
Skip to Search Results- 84Artificial Intelligence
- 23Machine Learning
- 17Games
- 11Reinforcement Learning
- 8Planning
- 7Computer Games
- 4Müller, Martin
- 3Mueller, Martin
- 2Burch, Neil
- 2Johanson, Michael
- 2Nakhost, Hootan
- 2Pelletier, Francis J.
- 63Graduate and Postdoctoral Studies (GPS), Faculty of
- 63Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 18Computing Science, Department of
- 18Computing Science, Department of/Technical Reports (Computing Science)
- 5Toolkit for Grant Success
- 4WISEST Summer Research Program
- 63Thesis
- 20Report
- 9Research Material
- 5Conference/Workshop Poster
- 2Review
- 1Conference/Workshop Presentation
-
Fall 2022
Medical Fake News is a pervasive part of the information that people consume on the internet. It may lead people to take actions which may put the lives of their family and community in danger - such actions include vaccine hesitancy, administering unverified and harmful treatments, etc. First...
-
Spring 2017
With the growing population of the elderly and the decline of population growth rate, developed countries are facing problems in taking care of their elderly. One of the issues that is becoming more severe is the issue of companionship for the aged people, particularly those who chose to live...
-
Fall 2023
The increasing popularity of Deep Neural Networks (DNN) has led to their application to many domains, including Music Generation. However, these large DNN-based models are heavily dependent on their training dataset, which means they perform poorly on musical genres that are out-of-distribution...
-
2019-10-01
SSHRC IG awarded 2020: The global economy is on the verge of a profound transformation as artificial intelligence (AI) achieves and exceeds human-level abilities in a growing number of domains. Canada is already a world leader in the development and commercialization of AI technologies. However,...
-
Fall 2020
This thesis is offered as a step forward in our understanding of forgetting in artificial neural networks. ANNs are a learning system loosely based on our understanding of the brain and are responsible for recent breakthroughs in artificial intelligence. However, they have been reported to be...
-
Spring 2020
Reinforcement learning (RL) is a powerful learning paradigm in which agents can learn to maximize sparse and delayed reward signals. Although RL has had many impressive successes in complex domains, learning can take hours, days, or even years of training data. A major challenge of contemporary...
-
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...
-
Fall 2015
Extensive-form games are a powerful framework for modeling sequential multi-agent interactions. In extensive-form games with imperfect information, Nash equilibria are generally used as a solution concept, but computing a Nash equilibrium can be intractable in large games. Instead, a variety of...
-
Spring 2023
Many competitive online video games release new characters on a regular basis. Designing these characters requires significant effort on several aspects including art, story, music, and game balance. Thus automating the design of these aspects offers value in saving human effort. This thesis...