Distribution shifts from sim2real gaps and controller–abstraction coupling

Address distribution shifts in statistical verification and control caused by (i) simulation-to-reality gaps and (ii) couplings between controllers and statistical abstractions that induce dependence and shift between calibration and deployment data; develop methods to quantify, compensate for, or guarantee safety under such shifts.

Background

Conformal prediction relies on exchangeability between calibration and test data. In practice, calibration often comes from simulators, leading to sim2real gaps, and control policies may affect the data used to build abstractions, creating couplings that break independence.

The authors emphasize dealing with these shifts as core open problems to enable reliable formal verification and control in realistic deployments.