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Subject: Agent
Departments: Department of Computing Science
Item type: Thesis
Languages: English
Collections: Graduate and Postdoctoral Studies (GPS), Faculty of
Collections: Graduate and Postdoctoral Studies (GPS), Faculty of /Theses and Dissertations
Supervisors: Bowling, Michael (Computing Science)
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Spring 2014
Efficient, unbiased estimation of agent performance is essential for drawing statistically significant conclusions in multi-agent domains with high outcome variance. Naive Monte Carlo estimation is often insufficient, as it can require a prohibitive number of samples, especially when evaluating...
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