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authorCamil Staps2017-10-23 13:06:40 +0200
committerCamil Staps2017-10-23 13:06:40 +0200
commit3b3f2e4ccfed3a63e9f815f379e68789b1a8f15e (patch)
treeca43d6f2ddd37e13d28956c22f0ba16e1ec0fe62
parentCleanup (diff)
1.1.4
-rw-r--r--assignments/assignment2/assignment2.tex8
1 files changed, 8 insertions, 0 deletions
diff --git a/assignments/assignment2/assignment2.tex b/assignments/assignment2/assignment2.tex
index 9fb455b..26e964e 100644
--- a/assignments/assignment2/assignment2.tex
+++ b/assignments/assignment2/assignment2.tex
@@ -63,6 +63,14 @@
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