Applying Genetic Programming for the Inverse Lindenmayer Problem

Abstract

The aim of this work is to find an automated solution for the Inverse Lindenmayer problem - that is to find the describing system for a given end-result of an L-system - using both Bacterial Programming and other related algorithms. To achieve this, several well-known L-systems were considered, their building symbols taken as the inputs for each algorithm, and the evolution results were compared with the formal definition of each system. The results indicate that this is indeed a viable area of research, as both Bacterial Programming and other different algorithms could be fitted to reverse engineer all of the considered systems.