Using genetic algorithms to improve the visual quality of fractal plants generated with CSG-PL-Systems

PL-systems are a powerful and flexible technique for plant modeling. Unfortunately it is a hard task to specify a PL-system, that generates a desired plant. Especially the tuning of the parameter values is time consuming and demands a lot of experience from the user. In this paper we describe how to apply genetic algorithms to CSG-PL-systems, which are a special class of PL-systems. A decomposition of CSG-PL-systems is introduced to extract those parts, which can serve as genotype. Mutation and mating, the two major operations of evolution techniques, are applied to this data set. With the described method it is possible to find easily natural looking individuals out of a species that is described in an abstract way by the underlying CSG-PL-system