We present the probabilistic model checker Storm. Storm supports the analysis of discrete-
and continuous-time variants of both Markov chains and Markov decision processes. Storm …

Abstract Model checking undiscounted reachability and expected-reward properties on
Markov decision processes (MDPs) is key for the verification of systems that act under …

Many infrastructure managers have the goal to increase the capacity of their railway
infrastructure due to an increasing demand. While methods for performance calculations of …

The de-facto standard approach in MDP verification is based on value iteration (VI). We
propose compositional VI, a framework for model checking compositional MDPs, that …

We revisit the symbolic verification of Markov chains with respect to finite horizon
reachability properties. The prevalent approach iteratively computes step-bounded state …

The analysis of formal models that include quantitative aspects such as timing or
probabilistic choices is performed by quantitative verification tools. Broad and mature tool …

Computing schedulers that optimize reachability probabilities in MDPs is a standard
verification task. To address scalability concerns, we focus on MDPs that are compositionally …

Robust autonomy and interaction of robots with their environment, even in rare or new
situations, is an ultimate goal of robotics research. We settle on Statistical Model Checking …

We consider the challenge of policy simplification and verification in the context of policies
learned through reinforcement learning (RL) in continuous environments. In well-behaved …

Probabilistic model checking computes probabilities and expected values related to
designated behaviours of interest in Markov models. As a formal verification approach, it is …