MOVES Seminar 20 Nov 2008

Angluin-style Learning of NFA

 


Carsten Kern

 

Abstract:



We introduce NL* as a learning algorithm for inferring
non-deterministic finite-state automata using membership and
equivalence queries. More specifically, residual finite-state automata
(RFSA) are learned similar as in Angluin's popular L* algorithm, which
however learns deterministic finite-state automata (DFA). As RFSA can
be exponentially more succinct than DFA, RFSA are the preferable
choice for many learning applications.  We have implementatred our
algorithm and applied it to a collection of examples which confirm the
expected advantage of NL* over L*.