Search Results for author: Jason Bernard

Found 4 papers, 0 papers with code

Stochastic L-system Inference from Multiple String Sequence Inputs

no code implementations29 Jan 2020 Jason Bernard, Ian McQuillan

Lindenmayer systems (L-systems) are a grammar system that consist of string rewriting rules.

Techniques for Inferring Context-Free Lindenmayer Systems With Genetic Algorithm

no code implementations15 May 2019 Jason Bernard, Ian McQuillan

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.

New Techniques for Inferring L-Systems Using Genetic Algorithm

no code implementations1 Dec 2017 Jason Bernard, Ian McQuillan

Indeed, while existing approaches are limited to L-systems with a total sum of 20 combined symbols in the productions, PMIT can infer almost all L-systems tested where the total sum is 140 symbols.

Cannot find the paper you are looking for? You can Submit a new open access paper.