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Evolving 3 D Models of Trees Using Genetic Programming

This paper describes a technique to evolve 3D models of plants based on deterministic automata. It uses cellular encoding to obtain these automata from trees evolved in standard genetic programming software. The fitness is a combination of high-level characteristics of the model, including overall shape, number of branches and geometric characteristics. We introduce a grid-based constraint evaluation as a way for the designer to shape a tree. This approach can be extended to modeling more than plants.