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- 3Machine learning
- 1Agent modelling
- 1Artificial intelligence
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- 1Catastrophic Forgetting
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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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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...
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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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Spring 2022
In this dissertation, we study online off-policy temporal-difference learning algorithms, a class of reinforcement learning algorithms that can learn predictions in an efficient and scalable manner. The contributions of this dissertation are one of the two kinds: (1) empirically studying existing...
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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 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...