The current industrial scenario has witnessed the application of several artificial intelligence-
based technologies for mining and processing IoMT-based big data. An emerging …

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 …

Recent advances in metric, semantic, and topological mapping have equipped autonomous
robots with concept grounding capabilities to interpret natural language tasks. Leveraging …

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

Plenty of novel emerging technologies are being proposed and evaluated today, mostly at
the device and circuit levels. It is unclear what the impact of different new technologies at the …

We provide a memory-efficient algorithm for multi-objective model checking problems on
Markov decision processes (MDPs) with multiple cost structures. The key problem at hand is …

Probabilistic model checking (PMC) is a well-established method for the quantitative
analysis of dynamic systems. Description logics (DLs) provide a well-suited formalism to …

The complexity of socio-technical systems using Ambient Intelligence (AmI) and the Internet
of Things (IoT) is growing exponentially, involving numerous entities, such as humans …

We provide an efficient algorithm for multi-objective model-checking problems on Markov
decision processes (MDPs) with multiple cost structures. The key problem at hand is to …

The detection of interactions is a challenging task present in almost all stages of software
development. In feature-oriented system design, this task is mainly investigated for …