Information entropy as an anthropomorphic concept

TL;DR

This paper explores the anthropomorphic nature of entropy, generalizes Shannon's information entropy, and demonstrates its applications in password complexity and genetic algorithm diversity analysis.

Contribution

It introduces a generalized framework for Shannon's entropy inspired by physical entropy's anthropomorphic perspective.

Findings

Entropy can be used to compare password complexity.

Entropy serves as a measure of diversity in genetic algorithms.

The generalized entropy aligns with physical entropy concepts.

Abstract

According to E.T. Jaynes and E.P. Wigner, entropy is an anthropomorphic concept in the sense that in a physical system correspond many thermodynamic systems. The physical system can be examined from many points of view each time examining different variables and calculating entropy differently. In this paper we discuss how this concept may be applied in information entropy; how Shannon's definition of entropy can fit in Jayne's and Wigner's statement. This is achieved by generalizing Shannon's notion of information entropy and this is the main contribution of the paper. Then we discuss how entropy under these considerations may be used for the comparison of password complexity and as a measure of diversity useful in the analysis of the behavior of genetic algorithms.