Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise

Résumé

Angluin's L* algorithm learns the minimal (complete) deterministic finite automaton (DFA) of a regular language using membership and equivalence queries. Its probabilistic approximatively correct (PAC) version substitutes an equivalence query by a large enough set of random membership queries to get a high level confidence to the answer. Thus it can be applied to any kind of (also non-regular) device and may be viewed as an algorithm for synthesizing an automaton abstracting the behavior of the device based on observations. Here we are interested on how Angluin's PAC learning algorithm behaves for devices which are obtained from a DFA by introducing some noise. More precisely we study whether Angluin's algorithm reduces the noise and produces a DFA closer to the original one than the noisy device. We propose several ways to introduce the noise: (1) the noisy device inverts the classification of words w.r.t. the DFA with a small probability, (2) the noisy device modifies with a small probability the letters of the word before asking its classification w.r.t. the DFA, and (3) the noisy device combines the classification of a word w.r.t. the DFA and its classification w.r.t. a counter automaton. Our experiments were performed on several hundred DFAs. Our main contributions, bluntly stated, consist in showing that: (1) Angluin's algorithm behaves well whenever the noisy device is produced by a random process, (2) but poorly with a structured noise, and, that (3) almost surely randomness yields systems with non-recursively enumerable languages.
Fichier principal
Vignette du fichier
gandalf2022.pdf (671.74 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03794320 , version 1 (13-01-2023)

Identifiants

Citer

Igor Khmelnitsky, Serge Haddad, Lina Ye, Benoît Barbot, Benedikt Bollig, et al.. Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise. GandALF 2022 - 13th International Symposium on Games, Automata, Logics and Formal Verification, Sep 2022, Madrid, Spain. pp.81-96, ⟨10.4204/EPTCS.370.6⟩. ⟨hal-03794320⟩
66 Consultations
54 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More