Computers can’t jump? A quantitative approach for studying creative leaps
Inhaltsverzeichnis
Reference
Lior Noy, Yuval Hart, Natalie Andrew, Omer Ramote, Avi Mayo and Uri Alon: Computers can’t jump? A quantitative approach for studying creative leaps. In: Computational Creativity 2012 ICCC 2012.
DOI
Abstract
We present a novel quantitative approach for studying creative leaps. Participants explored the space of shapes composed of ten adjacent squares, searching for ‘interesting and beautiful’ shapes. By recording players’ actions we were able to quantitatively study aspects of their exploration process. In particular our goal is to identify populated sub-regions in the shape space and study the dynamics of ‘creative leaps’: a jump from one such area to anoth- er. We present here the experimental system, our methods of analysis and some preliminary results. We show that the network of shapes created by human participants is different from the class of networks created by applying a simple random-walk algorithm. Chosen shapes show an interesting negative correlation between their abundance and the probability to be chosen as beautiful. We further analyzed the human network unique signature using its network motifs profile. Intriguingly, this signature shows similar- ity to words-adjacency networks extracted from texts. Lastly, we find preliminary evidence that human players exhibit two types of exploration: ‘scavenging’, where shapes similar in their visual- iconic meaning are quickly accumulated, and ‘creative leaps’, where players shift to a new region in the shape space after a prolonged search. We plan to build upon this result to quantita- tively study creative processes in general and creative leaps in particular.
Extended Abstract
Bibtex
Used References
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