21 citations · 23 across the 3 of their papers we have counts for
3 papers
eess.SY2022★ 2 cited
Anderson Acceleration for Partially Observable Markov Decision Processes: A Maximum Entropy Approach
Mingyu Park, Jaeuk Shin, Insoon Yang
Partially observable Markov decision processes (POMDPs) is a rich mathematical framework that embraces a large class of complex sequential decision-making problems under uncertaint…
cs.RO2021★ 21 cited
Infusing model predictive control into meta-reinforcement learning for mobile robots in dynamic environments
Jaeuk Shin, Astghik Hakobyan, Mingyu Park +3
The successful operation of mobile robots requires them to adapt rapidly to environmental changes. To develop an adaptive decision-making tool for mobile robots, we propose a novel…
eess.SY2021
On Anderson acceleration for partially observable Markov decision processes
Melike Ermis, Mingyu Park, Insoon Yang
This paper proposes an accelerated method for approximately solving partially observable Markov decision process (POMDP) problems offline. Our method carefully combines two existin…