In recent years, formal methods have been extensively used in the design of autonomous
systems. By employing mathematically rigorous techniques, formal methods can provide …

Notions of transition invariants and closure certificates have seen recent use in the formal
verification of controlled dynamical systems against\omega-regular properties …

This letter proposes a data-driven framework to synthesize safety controllers for nonlinear
systems with finite input sets and unknown mathematical models. The proposed scheme …

This paper proposes DeepSynth, a method for effective training of deep reinforcement
learning agents when the reward is sparse or non-Markovian, but at the same time progress …

Construction of finite-state abstractions (aka symbolic abstractions) is a promising approach
for formal verification and controller synthesis of complex systems. Finite-state abstractions …

This letter is concerned with develo** a data-driven approach for learning control barrier
certificates (CBCs) and associated safety controllers for discrete-time input-affine nonlinear …

The problem of supervisor design for systems analyzed in cooperating pairs of subsystems
is studied. The supervisors realize the cooperation using only sensor and actuator data of …

In this work, we study verification and synthesis problems for safety specifications over
unknown discrete-time stochastic systems. When a model of the system is available, barrier …

Leveraging autonomous systems in safety-critical scenarios requires verifying their
behaviors in the presence of uncertainties and black-box components that influence the …

In this letter, we introduces a data-driven framework for synthesizing controllers that enforce
properties expressed by so-called universal co-Büchi automata (-UCA) over control systems …