Abstract
M.Sc. (Computer Science)
Modelling the geometry of a 3D plant for use in a virtual environment can be
highly laborious, and hence modelling a large collection of variations of the same
plant can be a difficult task. Procedural rule-based methods, such as L-Systems,
that generate plant geometry indirectly are powerful techniques for the modelling
of plants. However such methods often require expert knowledge and skill in order
to be used effectively. This dissertation explores a method for the modelling of
procedurally generated plants using an evolutionary algorithm. The model is based
on gene expression programming, and uses a hybrid of automated and interactive
fitness evaluation. In the model, organisms are represented with linear genomes
that can be expressed as L-Systems. The L-Systems can in turn be interpreted
as geometry for 3D plants. Several automated fitness functions are presented to
rate plants based on various topological and geometric attributes. These fitness
functions are used in conjunction with user-based, interactive fitness evaluation
in order to provide a comparison of different organisms. The model discussed in
this dissertation offers advantages over previous approaches to modelling plants
with evolutionary algorithms, and allows a user to quickly generate a population
of varied plants without requiring knowledge of the underlying L-Systems.