Parameter Search for Aesthetic Design and Composition
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This thesis is about algorithmic creation in the arts – where an artist, designer or composer uses
a formal generative process to assist in crafting forms and patterns – and approaches to finding
effective input parameter values to these generative processes for aesthetic ends.
Framed in three practical studies, approaches to navigating the aesthetic possibilities of generative
processes in sound and visuals are presented, and strategies for eliciting the preferences
of the consumers of the generated output are explored.
The first study presents a musical interface that enables navigation of the possibilities of a
stochastic generative process with respect to measures of subjective predictability. Through a
mobile phone version of the application, aesthetic preferences are crowd-sourced.
The second study presents an eye-tracking based framework for the exploration of the possibilities
afforded by generative designs; the interaction between the viewers’ gaze patterns and
the system engendering a fluid navigation of the state-space of the visual forms.
The third study presents a crowd-sourced interactive evolutionary system, where populations
of abstract colour images are shaped by thousands of preference selections from users worldwide
For each study, the results of analyses eliciting the attributes of the generated outputs – and
their associated parameter values – that are most preferred by the consumers/users of these systems
are presented.
Placed in a historical and theoretical context, a refined perspective on the complex interrelationships
between generative processes, input parameters and perceived aesthetic value is
presented.
Contributions to knowledge include identified trends in objective aesthetic preferences in
colour combinations and their arrangements, theoretical insights relating perceptual mechanisms
to generative system design and analysis, strategies for effectively leveraging evolutionary computation
in an empirical aesthetic context, and a novel eye-tracking based framework for the
exploration of visual generative designs.
Authors
Oldfeldt Ek´eus, Henrik Carl-Olof JulianCollections
- Theses [3930]