In this paper, we relax the assumption of a known time horizon in optimal control models.

In the paper one and two-dimensional optimal control systems with perturbations are considered. Some sufficient conditions under which optimal processes continuously (or semicontinuously) depend on variable parameters of the system are proved.

This paper presents simple sufficient conditions under which optimal bunches in adverse-selection principal-agent problems can be characterized without using optimal control theory.

In advancing our prior work on a unified theory for pseudospectral (PS) optimal control, we present new results for PS methods over arbitrary grids. These results provide a way to compare performances among different PS methods and suggest guidelines to choose the proper grids and discretization approaches for solving optimal control problems. The new unified ideas reveal hidden properties of d...

We consider multi-objective convex optimal control problems. First we state a relationship between the (weakly or properly) efficient set of the multi-objective problem and the solution of the problem scalarized via a convex combination of objectives through a vector of parameters (or weights). Then we establish that (i) the solution of the scalarized (parametric) problem for any given paramete...

xvi 1 Optimal Control Theory 1 1.

An optimal control problem on a special nilpotent4-dimensional Lie group is discussed and some of its dynamical and geometrical properties are pointed out.

While stochastic optimal control, together with associate formulations like Reinforcement Learning, provides a formal approach to, amongst other, motor control, it remains computationally challenging for most practical problems. This thesis is concerned with the study of relations between stochastic optimal control and probabilistic inference. Such dualities – exemplified by the classical Kalma...