2 citations · 3 across the 11 of their papers we have counts for
Showing eess.SYShow all
2 papers · 1 filter
eess.SY2024★ 2 cited
SEEV: Synthesis with Efficient Exact Verification for ReLU Neural Barrier Functions
Hongchao Zhang, Zhizhen Qin, Sicun Gao +1
Neural Control Barrier Functions (NCBFs) have shown significant promise in enforcing safety constraints on nonlinear autonomous systems. State-of-the-art exact approaches to verify…
eess.SY2024
Hamilton-Jacobi Reachability in Reinforcement Learning: A Survey
Milan Ganai, Sicun Gao, Sylvia Herbert
Recent literature has proposed approaches that learn control policies with high performance while maintaining safety guarantees. Synthesizing Hamilton-Jacobi (HJ) reachable sets ha…