The algorithmic beauty of plants
The algorithmic beauty of plants
Fractal modelling: growth and form in biology
Fractal modelling: growth and form in biology
Illustrating evolutionary computation with Mathematica
Illustrating evolutionary computation with Mathematica
On Genetic Algorithms and Lindenmayer Systems
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
An L-System-Based Plant Modeling Language
AGTIVE '99 Proceedings of the International Workshop on Applications of Graph Transformations with Industrial Relevance
Database technologies for L-system simulations in virtual plant applications on bioinformatics
Knowledge and Information Systems
Grammatical evolution of L-systems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
An Approach to Derive Parametric L-System Using Genetic Algorithm
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
FranksTree: a genetic programming approach to evolve derived bracketed l-systems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Emergent diversity in an open-ended evolving virtual community
Artificial Life
| Hi-index | 0.00 |
L-systems are widely used in the modelling of branching structures and the growth process of biological objects such as plants, nerves and airways in lungs. The derivation of such L-system models involves a lot of hard mental work and time-consuming manual procedures. A method based on genetic algorithms for automating the derivation of L-systems is presented here. The method involves representation of branching structure, translation of L-systems to axial tree architectures, comparison of branching structure and the application of genetic algorithms. Branching structures are represented as axial trees and positional information is considered as an important attribute along with length and angle in the database configuration of branches. An algorithm is proposed for automatic L-system translation that compares randomly generated branching structures with the target structure. Edit distance, which is proposed as a measure of dissimilarity between rooted trees, is extended for the comparison of structures represented in axial trees and positional information is involved in the local cost function. Conventional genetic algorithms and repair mechanics are employed in the search for L-system models having the best fit to observational data.