Computational Creativity and Aesthetics with Algorithmic Information Theory

We build an analysis based on the Algorithmic Information Theory of computational creativity and extend it to revisit computational aesthetics, thereby, improving on the existing efforts of its formulation. We discuss Kolmogorov complexity, models and randomness deficiency (which is a measure of how...

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Vydané v:Entropy (Basel, Switzerland) Ročník 23; číslo 12; s. 1654
Hlavní autori: Mondol, Tiasa, Brown, Daniel G.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland MDPI AG 08.12.2021
MDPI
Predmet:
Aesthetics
algorithmic information theory
Algorithms
computational aesthetics
computational complexity
computational creativity
Creative process
Creativity
Information theory
Kolmogorov complexity
typicality novelty and value
computational creativity
typicality novelty and value
computational aesthetics
algorithmic information theory
Kolmogorov complexity
computational complexity
ISSN:1099-4300, 1099-4300
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Popis
Shrnutí:We build an analysis based on the Algorithmic Information Theory of computational creativity and extend it to revisit computational aesthetics, thereby, improving on the existing efforts of its formulation. We discuss Kolmogorov complexity, models and randomness deficiency (which is a measure of how much a model falls short of capturing the regularities in an artifact) and show that the notions of typicality and novelty of a creative artifact follow naturally from such definitions. Other exciting formalizations of aesthetic measures include logical depth and sophistication with which we can define, respectively, the value and creator’s artistry present in a creative work. We then look at some related research that combines information theory and creativity and analyze them with the algorithmic tools that we develop throughout the paper. Finally, we assemble the ideas and their algorithmic counterparts to complete an algorithmic information theoretic recipe for computational creativity and aesthetics.
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This paper is an extended version of our paper published in the Twelfth International Conference on Computational Creativity, Mexico City, Mexico (Virtual), 14–18 September 2021.
ISSN:1099-4300
1099-4300
DOI:10.3390/e23121654