Nonparametric Bayesian Approaches for Reinforcement Learning in Partially Observable Domains
نویسنده
چکیده
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 decisionmaking in complex, realworld domains.
منابع مشابه
Thesis Summary: Nonparametric Bayesian Approaches for Reinforcement Learning in Partially Observable Domains
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 decisionmaking in complex, realworld domains.
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