# Techniques for Inferring Context-Free Lindenmayer Systems With Genetic Algorithm

arXiv: https://arxiv.org/abs/1906.08860 · HTML: https://mlsanity.com/paper/1906.08860/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 May 2019.

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

- [Optimal L-Systems for Stochastic L-system Inference Problems](https://mlsanity.com/paper/2409.02259/) (2024)
- [Stringological sequence prediction I: efficient algorithms for predicting highly repetitive sequences](https://mlsanity.com/paper/2603.26852/) (2026)
- [A Graph-Based Classical and Quantum Approach to Deterministic L-System Inference](https://mlsanity.com/paper/2411.19906/) (2024)

## Abstract (arXiv)

Lindenmayer systems (L-systems) are a formal grammar system, where the most notable feature is a set of rewriting rules that are used to replace every symbol in a string in parallel; by repeating this process, a sequence of strings is produced. Some symbols in the strings may be interpreted as instructions for simulation software. Thus, the sequence can be used to model the steps of a process. Currently, creating an L-system for a specific process is done by hand by experts through much effort. The inductive inference problem attempts to infer an L-system from such a sequence of strings generated by an unknown system; this can be thought of as an intermediate step to inferring from a sequence of images. This paper evaluates and analyzes different genetic algorithm encoding schemes and mathematical properties for the L-system inductive inference problem. A new tool, the Plant Model Inference Tool for Context-Free L-systems (PMIT-D0L) is implemented based on these techniques. PMIT-D0L has been successfully evaluated on 28 known L-systems, with alphabets up to 31 symbols and a total sum of 281 symbols across the rewriting rules. PMIT-D0L can infer even the largest of these L-systems in less than a few seconds.