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The learned model also contains states, therefore they must be equivalent.
\item
+ A counter-example $\pi$ consists of a prefix, an input where an inconsistency appears and a suffix showing the inconsistency:
+ $\pi = \sigma u \rho$.
+ However, when we provide some sequence $\pi$ it may be possible to find distinct partitions
+ $\pi = \sigma_1 u_1 \rho_1 \neq \sigma_2 u_2 \rho_2 = \pi$
+ which both help to improve the hypothesis.
+ If on the first run we add $\rho_1$ to the suffices of our table,
+ $\sigma_2 u_2 \rho_2$ may not be covered yet,
+ and we may be able to add $\pi$ a second time.
\item