A sampling-based method constructs interval Markov decision process abstractions for nonlinear stochastic systems, enabling synthesis of control policies with PAC reach-avoid guarantees.
Probabilistic reachability and safety for controlled discrete time stochastic hybrid systems
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Data-Driven Yet Formal Policy Synthesis for Stochastic Nonlinear Dynamical Systems
A sampling-based method constructs interval Markov decision process abstractions for nonlinear stochastic systems, enabling synthesis of control policies with PAC reach-avoid guarantees.