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

Internet

https://ntv.ifmo.ru/file/article/19638.pdf

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