1 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
Optimal Exploration for Model-Based RL in Nonlinear Systems
Andrew Wagenmaker, Guanya Shi, Kevin Jamieson
Learning to control unknown nonlinear dynamical systems is a fundamental problem in reinforcement learning and control theory. A commonly applied approach is to first explore the e…
Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
Exploration in unknown environments is a fundamental problem in reinforcement learning and control. In this work, we study task-guided exploration and determine what precisely an a…
Experimental Design for Regret Minimization in Linear Bandits
Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson
In this paper we propose a novel experimental design-based algorithm to minimize regret in online stochastic linear and combinatorial bandits. While existing literature tends to fo…
Active Learning for Identification of Linear Dynamical Systems
Andrew Wagenmaker, Kevin Jamieson
We propose an algorithm to actively estimate the parameters of a linear dynamical system. Given complete control over the system's input, our algorithm adaptively chooses the input…