# Learning Regular Languages over Large Ordered Alphabets

arXiv: https://arxiv.org/abs/1506.00482 · HTML: https://mlsanity.com/paper/1506.00482/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jun 2015.

## Built on by (most cited first, 3 of 3)

- [Automata Cascades: Expressivity and Sample Complexity](https://mlsanity.com/paper/2211.14028/) (2022)
- [Active Learning of Symbolic Automata Over Rational Numbers](https://mlsanity.com/paper/2511.12315/) (2025)
- [Learning Canonical Register Automata over Ordered Data Domains](https://mlsanity.com/paper/2608.18765/) (2026)

## Abstract (arXiv)

This work is concerned with regular languages defined over large alphabets, either infinite or just too large to be expressed enumeratively. We define a generic model where transitions are labeled by elements of a finite partition of the alphabet. We then extend Angluin's L* algorithm for learning regular languages from examples for such automata. We have implemented this algorithm and we demonstrate its behavior where the alphabet is a subset of the natural or real numbers. We sketch the extension of the algorithm to a class of languages over partially ordered alphabets.