Controllable and realistic traffic simulation is critical for develo** and verifying
autonomous vehicles. Typical heuristic-based traffic models offer flexible control to make …

Formal specifications play an essential role in the life-cycle of modern systems, both at the
time of their design and during their operation. Despite their importance, formal …

Building general-purpose robots that operate seamlessly in any environment, with any
object, and utilizing various skills to complete diverse tasks has been a long-standing goal in …

This paper proposes a novel nature-inspired meta-heuristic algorithm, named Snow Geese
Algorithm. It is inspired by the migratory behavior of snow geese and emulates the distinctive …

Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-
critical applications, but require rigorous testing before deployment. The complexity of these …

We tackle the challenging problem of multi-agent cooperative motion planning for complex
tasks described using signal temporal logic (STL), where robots can have nonlinear and …

Signal Temporal Logic (STL) provides a convenient way of encoding complex control
objectives for robotic and cyber-physical systems. The state-of-the-art in trajectory synthesis …

A current trend in research on multi-agent control systems is to consider high-level task
specifications that go beyond traditional control objectives and take into account the …

In this work, we propose a novel approach for integrating rules into traffic agent trajectory
prediction. Consideration of rules is important for understanding how people behave-yet, it …

We propose a framework based on Recurrent Neural Networks (RNNs) to determine an
optimal control strategy for a discrete-time system that is required to satisfy specifications …