Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples

Gail Weiss; Yoav Goldberg; Eran Yahav

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arXiv · 1711.09576

Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples

Gail Weiss·Yoav Goldberg·Eran Yahav

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Abstract

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.

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Gail Weiss, Yoav Goldberg, Eran Yahav. 2017-11-27. Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples. https://arxiv.org/abs/1711.09576

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