Treffer: Information Theory in Perception of Form: From Gestalt to Algorithmic Complexity

Title:
Information Theory in Perception of Form: From Gestalt to Algorithmic Complexity
Source:
Entropy ; Volume 27 ; Issue 4 ; Pages: 434
Publisher Information:
Multidisciplinary Digital Publishing Institute
Publication Year:
2025
Collection:
MDPI Open Access Publishing
Document Type:
Fachzeitschrift text
File Description:
application/pdf
Language:
English
Relation:
Information Theory, Probability and Statistics; https://dx.doi.org/10.3390/e27040434
DOI:
10.3390/e27040434
Accession Number:
edsbas.E4D0AF8
Database:
BASE

Weitere Informationen

In 1948, Claude Shannon published a revolutionary paper on communication and information in engineering, one that made its way into the psychology of perception and changed it for good. However, the path to truly successful applications to psychology has been slow and bumpy. In this article, we present a readable account of that path, explaining the early difficulties as well as the creative solutions offered. The latter include Garner’s theory of sets and redundancy as well as mathematical group theory. These solutions, in turn, enabled rigorous objective definitions to the hitherto subjective Gestalt concepts of figural goodness, order, randomness, and predictability. More recent developments enabled the definition of, in an exact mathematical sense, the key notion of complexity. In this article, we demonstrate, for the first time, the presence of the association between people’s subjective impression of figural goodness and the pattern’s objective complexity. The more attractive the pattern appears to perception, the less complex it is and the smaller the set of subjectively similar patterns.