Computing Semicommutation Closures: a Machine Learning Approach

Maxime Bride (1) , Pierre-Cyrille Héam (2, 1) , Isabelle Jacques (2)

1 CASSIS - Combination of approaches to the security of infinite states systems
2 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

Semicommutation relations are simple rewriting relation on finite words using rules of the form ab → ba. In this paper we present how to use Angluin style machine learning algorithms to compute the image of regular language by the transitive closure of a semicommutation relation.

Domaines: Informatique et langage [cs.CL]

Maxime Bride, Pierre-Cyrille Héam, Isabelle Jacques. Computing Semicommutation Closures: a Machine Learning Approach. [Research Report] FEMTO-ST. 2014. ⟨hal-01087740⟩