Group: LearnLib

Support for parallel membership queries and thread-safe caches

Filters for collecting statistical data

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.

Common interfaces providing features supported by various learning algorithms

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

Data- and utility classes for Observation Tables

Basic Test Driver Generation Support

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 Howar, Bernhard Steffen, and Tiziana Margaria.

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

This artifact provides the implementation of (a blue-fringe version of) the "regular positive negative inference" (RPNI) learning algorithm as presented in the paper "Inferring regular languages in polynomial update time" (https://dx.doi.org/10.1142/9789812797902_0004) by Jose Oncina and Pedro García. More details on the blue-fringe version of this algorithm can be found in the book "Grammatical Inference" (https://doi.org/10.1017/CBO9781139194655) by Colin de la Higuera.

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, Falk Howar, and Bernhard Steffen.

A collection of utility methods to parse LearnLib specific settings

This artifact provides the implementations of various learning algorithms based on the "optimal MAT learning" concept as described in the paper "Active Automata Learning as Black-Box Search and Lazy Partition Refinement" (https://doi.org/10.1007/978-3-031-15629-8_17) by Falk Howar and Bernhard Steffen.

A collection of emptiness oracles

Translation utilities for mapping abstract hypothesis symbols to concrete SUL symbols

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" (https://dx.doi.org/10.17877/DE290R-16359) by Malte Isberner.

Reuse Tree for (intelligently) caching membership queries

A learning algorithm, which distinguishes hypothesis states using a discrimination tree (visibly push-down automata variant).

Group LearnLib Distribution

This artifact provides the implementation of the "onward subsequential transducer inference algorithm" (OSTIA) learning algorithm as presented in the paper "Learning Subsequential Transducers for Pattern Recognition Interpretation Tasks" (https://doi.org/10.1109/34.211465) by Jose Oncina, Pedro García, and Enrique Vidal.