27 citations · 78 across the 13 of their papers we have counts for
3 papers · 1 filter
Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms
Jinyang Jiang, Jiaqiao Hu, Yijie Peng
Classical reinforcement learning (RL) aims to optimize the expected cumulative reward. In this work, we consider the RL setting where the goal is to optimize the quantile of the cu…
Quantile-Based Policy Optimization for Reinforcement Learning
Jinyang Jiang, Jiaqiao Hu, Yijie Peng
Classical reinforcement learning (RL) aims to optimize the expected cumulative rewards. In this work, we consider the RL setting where the goal is to optimize the quantile of the c…
Ranking and Selection as Stochastic Control
Yijie Peng, Edwin K. P. Chong, Chun-Hung Chen +1
Under a Bayesian framework, we formulate the fully sequential sampling and selection decision in statistical ranking and selection as a stochastic control problem, and derive the a…