We survey the complexity class $\exists\mathbb {R} $, which captures the complexity of
deciding the existential theory of the reals. The class $\exists\mathbb {R} $ has roots in two …

Markov decision processes can be viewed as transformers of probability distributions. While
this view is useful from a practical standpoint to reason about trajectories of distributions …

We study distributional reachability for finite Markov decision processes (MDPs) from a
control theoretical perspective. Unlike standard probabilistic reachability notions, which are …

The Skolem problem is a long-standing open problem in linear dynamical systems: can a
linear recurrence sequence (LRS) ever reach 0 from a given initial configuration? Similarly …

The research field of optimization under uncertainty, even though already established in the
middle of the last century, gained much attention in the last two decades. The necessity to …

This work studies computation tree logic (CTL) model checking for finite-state Markov
decision processes (MDPs) over the space of their distributions. Instead of investigating …

We consider two-player stochastic games played on a finite graph for infinitely many rounds.
Stochastic games generalize both Markov decision processes (MDP) by adding an …

Markov Decision Processes (MDPs) are a classical model for decision making in the
presence of uncertainty. Often they are viewed as state transformers with planning …

We consider two-player stochastic games played on a finite graph for infinitely many rounds.
Stochastic games generalize both Markov decision processes (MDP) by adding an …

Abstract Linear Recurrence Sequences (LRS) are a fundamental mathematical primitive for
a plethora of applications such as the verification of probabilistic systems, model checking …