Juncal Arbelaiz

Information-theoretic receding-horizon active learning of nonlinear dynamical systems

Accurately learning nonlinear dynamics from a finite-duration experiment requires the efficient collection of informative data. We address this challenge for stochastic controlled nonlinear dynamical systems whose state is observed along a single trajectory. Our goal is to reconstruct the unknown controlled state-incre...