Scalable safety verification with simultaneous accuracy and efficiency for high-dimensional systems

Develop safety verification techniques for high-dimensional dynamical systems that simultaneously achieve rigorous accuracy and computational efficiency, overcoming the curse of dimensionality that affects Hamilton–Jacobi reachability and mixed-integer programming-based verification approaches.

Background

The paper notes that gold-standard verification tools such as Hamilton–Jacobi reachability and MILP-based verification suffer from severe scalability issues, limiting their applicability to real-world, high-dimensional systems.

Although decomposition methods and neural approximations have been explored, the challenge remains to ensure both tight, reliable guarantees and computational efficiency in a unified, scalable framework.