DETERMINISTIC FINITE AUTOMATA LEARNING USING COUNTEREXAMPLE GUIDED ABSTRACTION REFINEMENT

DETERMINISTIC FINITE AUTOMATA LEARNING USING COUNTEREXAMPLE GUIDED ABSTRACTION REFINEMENT

Subject of Research. The paper studies minimum-sized deterministic finite automata inferring problem. A hybrid method is developed and implemented reducing the given problem to Boolean satisfiability (SAT) technique and at the same time applying a counterexample guided abstraction refinement approac...

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Bibliographic Details
Main Author:	Ilya T. Zakirzyanov
Format:	Article
Language:	English
Published:	Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University) 2020-07-01
Series:	Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki
Subjects:	deterministic finite automata inference boolean satisfiability counterexample guided abstraction refinement symmetry breaking grammatical inference
Online Access:	https://ntv.ifmo.ru/file/article/19638.pdf

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