  We present a novel algorithm that uses exact learning and abstraction to
extract a deterministic finite automaton describing the state dynamics of a
given trained RNN. We do this using Angluin's L* algorithm as a learner and the
trained RNN as an oracle. Our technique efficiently extracts accurate automata
from trained RNNs, even when the state vectors are large and require fine
differentiation.
