Explore More and Improve Regret in Linear Quadratic Regulators

Stabilizing the unknown dynamics of a control system and minimizing regret in control of an unknown system are among the main goals in control theory and reinforcement learning. In this work, we pursue both these goals for adaptive control of linear quadratic regulators (LQR)... (read more)

PDF Abstract
No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet