Ecosystems are complex and sparsely observed making inference and prediction
challenging. Empirical dynamic modelling (EDM) circumvents the need for a parametric …

A high school student can create deep Q-learning code to control her robot, without any
understanding of the meaning of'deep'or'Q', or why the code sometimes fails. This book is …

Many important applications in global optimization, algebra, probability and statistics,
applied mathematics, control theory, financial mathematics, inverse problems, etc. can be …

We consider the class of nonlinear optimal control problems (OCPs) with polynomial data,
ie, the differential equation, state and control constraints, and cost are all described by …

We study the relations between classical information and the feasibility of accurate
manipulation of quantum system dynamics. We show that if an efficient classical …

We provide a new method to approximate a (possibly discontinuous) function using
Christoffel–Darboux kernels. Our knowledge about the unknown multivariate function is in …

This article is about the data-driven computation of optimal control for a class of control affine
deterministic nonlinear systems. We assume that the control dynamical system model is not …

We investigate relationships between the deterministic infinite time horizon optimal control
problem with discounting, in which the state trajectories remain in a given compact set Y …

We study a convex optimization framework for bounding extreme events in nonlinear
dynamical systems governed by ordinary or partial differential equations (ODEs or PDEs) …

This paper is concerned with computational methods for Lyapunov-based stabilization of an
attractor set of a nonlinear dynamical system. Based upon a stochastic representation of …