A collection of algorithms for handling counterexamples in automata learning

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

This artifact provides the implementation of the L* learning algorithm described in the paper "Learning Regular Sets from Queries and Counterexamples" (https://doi.org/10.1016/0890-5401(87)90052-6) by Dana Angluin including variations ...

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 Observation-Pack learning algorithm as described in the PhD thesis "Active learning of interface programs" (http://doi.org/10.17877/DE290R-4817) by Falk Howar.

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.

A learning algorithm, which distinguishes hypothesis states using a discrimination tree.

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, ...

An artifact that aggregates all other artifacts of LearnLib to produce an Uber-JAR that can be used in non-maven environments. Likewise, this single artifact may be used in maven-aware environments to declare a dependency on all ...

This artifact provides the implementation of the VPA adaption of the Observation-Pack learning algorithm as discussed in the PhD thesis "Foundations of Active Automata Learning: An Algorithmic Perspective" ...

This artifact provides the implementations of various learning algorithms for systems of procedural automata such as the ones described in the papers "Compositional learning of mutually recursive procedural systems ...