Runtime Verification can be defined as a collection of formal methods for studying the
dynamic evaluation of execution traces against formal specifications. Aside from creating a …

This paper proposes a distributed model predictive control (DMPC) for a class of discrete-
time stochastic multi-agent systems subject to partially coupled temporal logic tasks. For …

We present a framework to interpret signal temporal logic (STL) formulas over discrete-time
stochastic processes in terms of the induced risk. Each realization of a stochastic process …

The wide availability of data coupled with the computational advances in artificial
intelligence and machine learning promise to enable many future technologies such as …

In recent years, Machine Learning (ML) models have achieved remarkable success in
various domains. However, these models also tend to demonstrate unsafe behaviors …

Composite event recognition (CER) systems process streams of sensor data and infer
composite events of interest by means of pattern matching. Data uncertainty is frequent in …

In this work, we present a novel robustness measure for continuous-time stochastic
trajectories with respect to Signal Temporal Logic (STL) specifications. We show the …

The robustness of signal temporal logic not only assesses whether a signal adheres to a
specification but also provides a measure of how much a formula is fulfilled or violated. The …

We define a logical framework that permits runtime verification to take place when a monitor
has incomplete or uncertain information about the underlying trace. Uncertainty is modeled …

We reformulate the signal temporal logic (STL) synthesis problem as a maximum a-
posteriori (MAP) inference problem. To this end, we introduce the notion of random STL …