Abstract The term Cyber-Physical Systems (CPS) typically refers to engineered, physical
and biological systems monitored and/or controlled by an embedded computational core …

Urban driving simulators, such as CARLA, provide 3-D environments and useful tools to
easily simulate sensorimotor control systems in scenarios with complex multi-agent …

In this paper, we present the Real-Time Analog Monitoring Tool (RTAMT), a tool for
quantitative monitoring of Signal Temporal Logic (STL) specifications. The library …

Deep reinforcement learning has become a popular technique to train autonomous agents
to learn control policies that enable them to accomplish complex tasks in uncertain …

Cyber-physical system applications such as autonomous vehicles, wearable devices, and
avionic systems generate a large volume of time-series data. Designers often look for tools …

Cyber-physical systems theory offers a powerful framework for modeling, analyzing, and
designing real engineering systems integrating communication, control, and computation …

In order to effectively analyze and build cyberphysical systems (CPS), designers today have
to combat the data deluge problem, ie, the burden of processing intractably large amounts of …

In this paper, we consider the problem of monitoring temporal patterns expressed in Signal
Temporal Logic (STL) over time-series data in a clairvoyant fashion. Existing offline or online …

Learning-from-demonstrations is an emerging paradigm to obtain effective robot control
policies for complex tasks via reinforcement learning without the need to explicitly design …

Monitoring of hybrid systems attracts both scientific and practical attention. However,
monitoring algorithms suffer from the methodological difficulty of only observing sampled …