Towards Efficient Active Learning of PDFA

06/17/2022

∙

by   Franz Mayr, et al.

∙

0

∙

share

We propose a new active learning algorithm for PDFA based on three main aspects: a congruence over states which takes into account next-symbol probability distributions, a quantization that copes with differences in distributions, and an efficient tree-based data structure. Experiments showed significant performance gains with respect to reference implementations.