A two-layer DP-PHA scheme approximates optimal policies in Bayesian RL by separating reducible from irreducible uncertainty, demonstrated on the LQG problem with unknown gain.
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Revised Progressive-Hedging-Algorithm Based Two-layer Solution Scheme for Bayesian Reinforcement Learning
A two-layer DP-PHA scheme approximates optimal policies in Bayesian RL by separating reducible from irreducible uncertainty, demonstrated on the LQG problem with unknown gain.