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Author: Bard, Nolan DC
Subject: Machine learning
Item type: Thesis
Collections: Graduate and Postdoctoral Studies (GPS), Faculty of
Collections: Graduate and Postdoctoral Studies (GPS), Faculty of /Theses and Dissertations
Supervisors: Michael Bowling (Department of Computing Science, University of Alberta)
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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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