3 papers
eess.SY2026
Reachability-Preserving Bellman Operator for the Discounted Reach-Cost Value Function: Uniting Hamilton-Jacobi Reachability and Reinforcement Learning
Isabelle El-Hajj, Prashant Solanki, Jasper van Beers +2
Hamilton-Jacobi (HJ) reachability provides rigorous safety and reachability guarantees for continuous-time dynamical systems, but its numerical solution suffers from the curse of d…
eess.SY2026
Certifying Hamilton-Jacobi Reachability Learned via Reinforcement Learning
Prashant Solanki, Isabelle El-Hajj, Jasper J. van Beers +2
We present a framework to \emph{certify} Hamilton--Jacobi (HJ) reachability learned by reinforcement learning (RL). Building on a discounted initial time \emph{travel-cost} formula…
eess.SY2025
Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets
Prashant Solanki, Nikolaus Vertovec, Yannik Schnitzer +3
Recent approaches to leveraging deep learning for computing reachable sets of continuous-time dynamical systems have gained popularity over traditional level-set methods, as they o…