54 citations · 217 across the 13 of their papers we have counts for
5 papers · 1 filter
Observational Overfitting in Reinforcement Learning
Xingyou Song, Yiding Jiang, Stephen Tu +2
A major component of overfitting in model-free reinforcement learning (RL) involves the case where the agent may mistakenly correlate reward with certain spurious features from the…
A Tutorial on Concentration Bounds for System Identification
Nikolai Matni, Stephen Tu
We provide a brief tutorial on the use of concentration inequalities as they apply to system identification of state-space parameters of linear time invariant systems, with a focus…
From self-tuning regulators to reinforcement learning and back again
Nikolai Matni, Alexandre Proutiere, Anders Rantzer +1
Machine and reinforcement learning (RL) are increasingly being applied to plan and control the behavior of autonomous systems interacting with the physical world. Examples include…
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
Karl Krauth, Stephen Tu, Benjamin Recht
We study the sample complexity of approximate policy iteration (PI) for the Linear Quadratic Regulator (LQR), building on a recent line of work using LQR as a testbed to understand…
Certainty Equivalence is Efficient for Linear Quadratic Control
Horia Mania, Stephen Tu, Benjamin Recht
We study the performance of the certainty equivalent controller on Linear Quadratic (LQ) control problems with unknown transition dynamics. We show that for both the fully and part…