Information entropy as an anthropomorphic concept

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.

The paper contains some flaws. The definition joint entropy in comparison to join entropy as discussed in the paper is not correct

Information Theory (cs.IT); Artificial Intelligence (cs.AI)

arXiv:1503.01967 [cs.IT]

(or arXiv:1503.01967v3 [cs.IT] for this version)

https://doi.org/10.48550/arXiv.1503.01967 Focus to learn more arXiv-issued DOI via DataCite

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