2 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
Self-Consistent Adjoint Policy Iteration for Constrained Dynamic Portfolio Choice
Jeonggyu Huh, Yeoneung Kim, Seungwon Jeong
We develop simulation-based policy iteration for continuous-time portfolio choice with predictable returns and convex constraints. Each outer step re-evaluates a fixed-latent open-…
Policy Iteration for Stationary Discounted Hamilton--Jacobi--Bellman Equations: A Viscosity Approach
Namkyeong Cho, Yeoneung Kim
We study policy iteration (PI) for deterministic infinite-horizon discounted control problems characterized by stationary Hamilton--Jacobi--Bellman equations. For general viscosity…
Hamilton-Jacobi Based Policy-Iteration via Deep Operator Learning
Jae Yong Lee, Yeoneung Kim
The framework of deep operator network (DeepONet) has been widely exploited thanks to its capability of solving high dimensional partial differential equations. In this paper, we i…
On the stability of Lipschitz continuous control problems and its application to reinforcement learning
Namkyeong Cho, Yeoneung Kim
We address the crucial yet underexplored stability properties of the Hamilton--Jacobi--Bellman (HJB) equation in model-free reinforcement learning contexts, specifically for Lipsch…