Artificial evolution for computer graphics
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Evolutionary Art and Computers
Evolutionary Art and Computers
Accelerating Evolution by Direct Manipulation for Interactive Fashion Design
ICCIMA '01 Proceedings of the Fourth International Conference on Computational Intelligence and Multimedia Applications
Multiobjective Satisfaction within an Interactive Evolutionary Design Environment
Evolutionary Computation
Aspects of Soft Computing, Intelligent Robotics and Control
Aspects of Soft Computing, Intelligent Robotics and Control
Aesthetic classification and sorting based on image compression
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Exploring collections of 3D models using fuzzy correspondences
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Guided exploration of physically valid shapes for furniture design
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Investigating aesthetic features to model human preference in evolutionary art
EvoMUSART'12 Proceedings of the First international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Trace selection for interactive evolutionary algorithms
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Evolutionary algorithms have shown themselves to be useful interactive design tools. However, current algorithms only receive feedback about candidate fitness at the whole-candidate level. In this paper we describe a model-free method, using sensitivity analysis, which allows designers to provide fitness feedback to the system at the component level. Any part of a candidate can be marked by the designer as interesting (i.e. having high fitness). This has the potential to improve the design experience in two ways: (1) The finer-grain guidance provided by partial selections facilitates more precise iteration on design ideas so the designer can maximize her energy and attention. (2) When steering the evolutionary system with more detailed feedback, the designer may discover greater feelings of satisfaction with and ownership over the final designs.