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Embracing the Bias of the Machine: Exploring Non-Human Fitness Functions
2012
Zenodo
Autonomous aesthetic evaluation is the Holy Grail of generative music, and one of the great challenges of computational creativity. Unlike most other computational activities, there is no notion of optimality in evaluating creative output: there are subjective impressions involved, and framing obviously plays a big role. When developing metacreative systems, a purely objective fitness function is not available: the designer is thus faced with how much of their own aesthetic to include. Can a
doi:10.5281/zenodo.4285436
fatcat:c4r23yddyfetzk3yavsdxhkrcm