Using Genetic Algorithms to Improve the Visual Quality of Fractal Plants Generated with CSG-PL-Systems
Inhaltsverzeichnis
Reference
Traxler, C., Gervautz, M. (1996). Using Genetic Algorithms to Improve the Visual Quality of Fractal Plants Generated with CSG-PL-Systems. Technical Report TR-186-2-96-04. Institute of Computer Graphics, Vienna University of Technology.
DOI
Abstract
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. Key Words: genetic algorithms, artificial evolution, CSG-PL-systems, natural phenomena 1 Introduction Genetic algorithms are a reliable and powerful search strategy to find sub-optimal solutions in huge data spaces. The principles of evolu...
Extended Abstract
Bibtex
Used References
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