Infrastructure and core functionalities of LearnLib

Support classes for easily writing integration test cases for learning algorithms

A collection of algorithms for handling counterexamples in automata learning

Membership and equivalence oracles using an automaton model as backend

Caches to avoid posing duplicate membership queries

A collection of basic algorithm for approximating equivalence queries

A flexible, optimized version of Dana Angluin's L* algorithm

Support for posing membership queries in parallel

This artifact provides the implementation of the learning algorithm described in the book "An Introduction to Computational Learning Theory" by Michael Kearns and Umesh Vazirani.

This artifact provides the implementation of the DHC learning algorithm as described in the paper "Automata Learning with on-the-Fly Direct Hypothesis Construction" (https://doi.org/10.1007/978-3-642-34781-8_19) by Maik Merten, Falk ...

This artifact provides the implementation of the TTT algorithm as described in the paper "The TTT Algorithm: A Redundancy-Free Approach to Active Automata Learning" (https://doi.org/10.1007/978-3-319-11164-3_26) by Malte Isberner, ...