Project Modules
This project has declared the following modules:
| Name | Description |
|---|---|
| LearnLib :: Algorithms :: ADT | The ADT Algorithm. Uses adaptive distinguishing trees (a generalization of adaptive distinguishing sequences) to separate hypothesis states and focuses on minimizing the amount of resets during the learning process. |
| LearnLib :: Algorithms :: DHC | The Direct Hypothesis Construction algorithm for active learning of Mealy machines |
| LearnLib :: Algorithms :: Discrimination Tree | A learning algorithm, which distinguishes hypothesis states using a discrimination tree. |
| LearnLib :: Algorithms :: Discrimination Tree [VPDA] | A learning algorithm, which distinguishes hypothesis states using a discrimination tree (visibly push-down automata variant). |
| LearnLib :: Algorithms :: Kearns/Vazirani | The automata learning algorithm described by Kearns & Vazirani |
| LearnLib :: Algorithms :: L* | A flexible, optimized version of Dana Angluin's L* algorithm. This module provides access to the original version of L*, extensions for Mealy machines, and variants with enhanced counterexample analysis (as proposed by e.g. Maler & Pnueli and Rivest & Schapire). |
| LearnLib :: Algorithms :: NL* | A variant of the L* algorithm for inferring non-deterministic hypothesis automata. |
| LearnLib :: Algorithms :: TTT | The TTT Algorithm |
| LearnLib :: Algorithms :: TTT [VPDA] | The TTT Algorithm (visibly push-down automata variant) |