15 citations · 17 across the 2 of their papers we have counts for
2 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.LG2020★ 15 cited
Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls
Jeongho Kim, Jaeuk Shin, Insoon Yang
In this paper, we propose Q-learning algorithms for continuous-time deterministic optimal control problems with Lipschitz continuous controls. Our method is based on a new class of…