scholarly journals On the Problem of Small Objects

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1524
Author(s):  
Daniel G. Brown ◽  
Tiasa Mondol

We discuss how to assess computationally the aesthetic value of “small” objects, namely those that have short digital descriptions. Such small objects still matter: they include headlines, poems, song lyrics, short musical scripts and other culturally crucial items. Yet, small objects are a confounding case for our recent work adapting ideas from algorithmic information theory (AIT) to the domain of computational creativity, as they cannot be either logically deep or sophisticated following the traditional definitions of AIT. We show how restricting the class of models under analysis can make it the case that we can still separate high-quality small objects from ordinary ones, and discuss the strengths and limitations of our adaptation.

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1654
Author(s):  
Tiasa Mondol ◽  
Daniel G. Brown

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.


2020 ◽  
Vol 2 (1) ◽  
pp. 32-35
Author(s):  
Eric Holloway

Leonid Levin developed the first stochastic conservation of information law, describing it as "torturing an uninformed witness cannot give information about the crime."  Levin's law unifies both the deterministic and stochastic cases of conservation of information.  A proof of Levin's law from Algorithmic Information Theory is given as well as a discussion of its implications in evolutionary algorithms and fitness functions.


2018 ◽  
Vol 11 (7) ◽  
pp. 54
Author(s):  
Elham Abdullah Rayes

The current study aimed at plasticizing contemporary artworks by activating the formal and denotative significances of the logo of NEOM through the concept of abstract art. To achieve the study objectives, participants were asked to plasticize contemporary artworks using multiple-sized canvas, several coloring materials, a computer and some software as a technological medium, and high-quality printer papers to activate the significances of the logo of NEOM. Abstract artworks were displayed and analyzed in the light of activating the formal and denotative significances of the logo of NEOM. The author follows the descriptive approach and the quasi-experimental approach. The experiment was applied to female students in the Arts Lab at Umm Al-Qura University in 2018/ 1439H. The experiment yielded the ability of activating the logo of NEOM in artworks (plastic works), combining the significances of the logo of NEOM and abstract art produces unusual artworks, plastically activating the logo of NEOM resulted in enriching the aesthetic value of artworks, and formal and denotative significances of the logo of NEOM enrich plastic arts especially abstract works. The author recommends keeping up with contemporary progress and events and inspiring plastic artworks from the reality around the artist.


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