4 papers
Online Bayesian Risk-Averse Reinforcement Learning
Yuhao Wang, Enlu Zhou
In this paper, we study the Bayesian risk-averse formulation in reinforcement learning (RL). To address the epistemic uncertainty due to a lack of data, we adopt the Bayesian Risk…
Ranking and Selection with Simultaneous Input Data Collection
Yuhao Wang, Enlu Zhou
In this paper, we propose a general and novel formulation of ranking and selection with the existence of streaming input data. The collection of multiple streams of such data may c…
Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate
Yifan Lin, Yuhao Wang, Enlu Zhou
Reinforcement learning provides a mathematical framework for learning-based control, whose success largely depends on the amount of data it can utilize. The efficient utilization o…
Fixed Confidence and Fixed Tolerance Bi-level Optimization for Selecting the Best Optimized System
Yuhao Wang, Seong-Hee Kim, Enlu Zhou
In this paper, we study a fixed-confidence, fixed-tolerance formulation of a class of stochastic bi-level optimization problems, where the upper-level problem selects from a finite…