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Nonparametric Bayesian Approaches for Reinforcement Learning in Partially Observable Domains
Last modified: 2010-07-05
Abstract
The objective of my doctoral research is bring together two fields: partially-observable reinforcement learning (PORL) and non-parametric Bayesian statistics (NPB) to address issues of statistical modeling and decision-making in complex, real-world domains.
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