Quantitative formal models capture probabilistic behaviour, real-time aspects, or general
continuous dynamics. A number of tools support their automatic analysis with respect to …

Stochastic hybrid automata (SHA) are a powerful tool to evaluate the dependability and
safety of critical infrastructures. However, the resolution of nondeterminism, which is present …

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 …

Success or failure of attacks on high-security systems, such as hacker attacks on sensitive
data, depend on various situational conditions, including the timing and success chances of …

This paper proposes an algorithm to maximize reachability probabilities for rectangular
automata with random clocks via a history-dependent prophetic scheduler. This model class …

Stochastic Hybrid automata (SHA) are increasingly used to evaluate the dependability and
safety of critical infrastructures. Nondeterminism, which is present in many purely hybrid …

This paper introduces two stochastic variants of rectangular automata. First, rectangular
automata with random events (RAE) are introduced, which semantically embed random …

In the formal verification of stochastic systems, statistical model checking uses simulation to
overcome the state space explosion problem of probabilistic model checking. Yet its runtime …

Optimal decision-making under stochastic uncertainty is a core problem tackled in artificial
intelligence/machine learning (AI), planning, and verification. Planning and AI methods aim …

Statistical model checking uses simulation to overcome the state space explosion problem
in formal verification. Yet its runtime explodes when faced with rare events, unless a rare …