Abstract:
Three dimensional model design is a well-known and studied field, with numerous real-world
applications. However, the manual construction of these models can often be time-consuming to the
average user, despite the advantages o ffered through computational advances. This thesis presents
an approach to the design of 3D structures using evolutionary computation and L-systems, which
involves the automated production of such designs using a strict set of fitness functions. These
functions focus on the geometric properties of the models produced, as well as their quantifiable
aesthetic value - a topic which has not been widely investigated with respect to 3D models. New
extensions to existing aesthetic measures are discussed and implemented in the presented system in
order to produce designs which are visually pleasing. The system itself facilitates the construction of
models requiring minimal user initialization and no user-based feedback throughout the evolutionary
cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a
relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration
into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented,
with a focus on both performance and visual results. Although subjective, these results o er insight
into future applications and study in the fi eld of computational aesthetics and automated structure
design.
