Robot control for tasks such as moving around obstacles or grasping objects has advanced
significantly in the last few decades. However, controlling robots to perform complex tasks is …

Stochastic hybrid systems have received significant attentions as a relevant modeling
framework describing many systems, from engineering to the life sciences: they enable the …

We propose to synthesize a control policy for a Markov decision process (MDP) such that the
resulting traces of the MDP satisfy a linear temporal logic (LTL) property. We construct a …

We consider synthesis of control policies that maximize the probability of satisfying given
temporal logic specifications in unknown, stochastic environments. We model the interaction …

We present a method for designing a robust control policy for an uncertain system subject to
temporal logic specifications. The system is modeled as a finite Markov Decision Process …

Symbolic approaches for control design construct finite-state abstract models that are related
to the original systems, then use techniques from finite-state synthesis to compute controllers …

Formal methods are increasingly being used for control and verification of dynamic systems
against complex specifications. In general, these methods rely on a relatively simple system …

This paper studies an optimal control problem for continuous-time stochastic systems
subject to objectives specified in a subclass of metric interval temporal logic specifications, a …

In the past few years there has been a growing interest in the use of symbolic models for
control systems. The main reason is the possibility to leverage algorithmic techniques over …

In this paper we propose a compositional framework for the construction of approximations
of the interconnection of a class of stochastic hybrid systems. As special cases, this class of …