Trajectory optimization under uncertainty underpins a wide range of applications in robotics.
However, existing methods are limited in terms of reasoning about sources of epistemic and …

In this article, we derive conditions for the existence of solutions to state-constrained
continuity inclusions in Wasserstein spaces whose right-hand sides may be discontinuous in …

We revisit the sample average approximation (SAA) approach for nonconvex stochastic
programming. We show that applying the SAA approach to problems with expected value …

The control theory is one of the most fundamental branches of engineering as it implicates
solving abilities of numerous non-linear engineering design problems efficiently. Again …

In this paper, we consider continuous-time stochastic optimal control problems where the
cost is evaluated through a coherent risk measure. We provide an explicit gradient descent …

We derive first-order Pontryagin optimality conditions for stochastic optimal control with
deterministic controls for systems modeled by rough differential equations (RDE) driven by …

In this paper, we investigate properties of solutions to a space-time fractional variable-order
conformable nonlinear differential equation with a generalized tempered fractional Laplace …

We derive a first order optimality condition for a class of agent-based systems, as well as for
their mean-field counterpart. A relevant difficulty of our analysis is that the state equation is …

In this paper, we consider continuous-time stochastic optimal control problems where the
cost is evaluated through a coherent risk measure. We provide an explicit gradient descent …

We propose a novel non-parametric learning paradigm for the identification of drift and
diffusion coefficients of multi-dimensional non-linear stochastic differential equations, which …