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Skip to Search Results- 11Online learning
- 3Machine learning
- 2Opponent modelling
- 1Agent modelling
- 1Artificial intelligence
- 1Bandits
- 1Bard, Nolan DC
- 1Bartók, Gábor
- 1Chen, Zhaorui
- 1Dogru, Oguzhan
- 1Hladky, Stephen Michael
- 1Huang, Ruitong
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Fall 2009
Commercial video game developers constantly strive to create intelligent humanoid characters that are controlled by computers. To ensure computer opponents are challenging to human players, these characters are often allowed to cheat. Although they appear skillful at playing video games,...
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Motivation and the information behaviours of online learning students: the case of a professionally-oriented, graduate program
DownloadFall 2010
Online learning is a wonderful opportunity for students who cannot attend classes at conventional times and places to further their education. However, to some extent, accessing and sharing information is often quite different and potentially more difficult for this particular group (e.g., they...
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Spring 2011
Current statistics suggest women form the majority of online learners. Their enrollment levels may be a result of promotional materials suggesting online learning allows learners access to flexible learning opportunities that will complement their busy lives. This research questions those...
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Fall 2012
In a partial-monitoring game a player has to make decisions in a sequential manner. In each round, the player suffers some loss that depends on his decision and an outcome chosen by an opponent, after which he receives "some" information about the outcome. The goal of the player is to keep the...
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Spring 2014
The culture of the young may increasingly be seen as a harbinger enticing us to follow a pathway from which will emerge the re-conceptualized educational practices of a new century. This research set out to discover where the highways of the Internet would lead me, the researcher-practitioner, in...
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Spring 2016
Ideal agent behaviour in multiagent environments depends on the behaviour of other agents. Consequently, acting to maximize utility is challenging since an agent must gather and exploit knowledge about how the other (potentially adaptive) agents behave. In this thesis, we investigate how an...
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Fall 2016
In an online learning problem a player makes decisions in a sequential manner. In each round, the player receives some reward that depends on his action and an outcome generated by the environment while some feedback information about the outcome is revealed. The goal of the player can be...
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Fall 2017
On the one hand, theoretical analyses of machine learning algorithms are typically performed based on various probabilistic assumptions about the data. While these probabilistic assumptions are important in the analyses, it is debatable whether such assumptions actually hold in practice. Another...
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Recommender systems to support socio-collaborative learning in educational discussion forums
DownloadFall 2020
With the popularity of online education, many educational technologies have been introduced to support students' learning. Among them, asynchronous discussion forums are widely used to support students’ socio-collaborative learning processes. However, the forum's complex thread structure and...
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Fall 2020
Learning online is essential for an agent to perform well in an ever-changing world. An agent has to learn online not only out of necessity --- a non-stationary world might render past learning useless --- but also because continual tracking in a temporally coherent world can result in better...