Search Results for author: MinGyu Park

Found 2 papers, 0 papers with code

Anderson Acceleration for Partially Observable Markov Decision Processes: A Maximum Entropy Approach

no code implementations28 Nov 2022 MinGyu Park, Jaeuk Shin, Insoon Yang

Inspired by the quasi-Newton interpretation of AA, we propose a maximum entropy variant of QMDP, which we call soft QMDP, to fully benefit from AA.

Decision Making

On Anderson acceleration for partially observable Markov decision processes

no code implementations29 Mar 2021 Melike Ermis, MinGyu Park, Insoon Yang

This paper proposes an accelerated method for approximately solving partially observable Markov decision process (POMDP) problems offline.

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