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Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression
In this article, we develop a framework for verifying partially-observable, discrete-time dynamical systems with unmodelled dynamics against temporal logic specifications from a given input-output dataset.
Synergistic Offline-Online Control Synthesis via Local Gaussian Process Regression
The online controller may improve the baseline guarantees since it avoids the discretization error and reduces regression error as new data is collected.
Strategy Synthesis for Partially-known Switched Stochastic Systems
We present a data-driven framework for strategy synthesis for partially-known switched stochastic systems.
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