FLJun 17, 2022
Towards Efficient Active Learning of PDFAFranz Mayr, Sergio Yovine, Federico Pan et al.
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.