On the Problem of Small Objects

Abstract

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.

Computational Creativity and Aesthetics with Algorithmic Information Theory

“…Since M describes a set of objects, in most cases, it is almost bound to be larger than x itself (the complexity of a sensible model for a set of haikus will almost surely be larger than any individual , as haikus are small objects and not very compressible [ 23 ]). Hence, a complexity restriction is imposed on M such that .…”

“…If we enforce properties, such as injection or monotony on the total function, we essentially create a method that can generate creative artifacts with a certain style embellishments ( p ) upon receiving influences ( d ) from the environment. Furthermore, by using a UTM with two prefix-free input tapes, we can analyze how likely an artifact x is a product of a creator simulated by a program p by analyzing the likelihood of obtaining a prefix-free d in fair coin tosses [ 23 , 39 ].…”