English

Contracting and Involutive Negations of Probability Distributions

Artificial Intelligence 2021-03-31 v1

Abstract

A dozen papers have considered the concept of negation of probability distributions (pd) introduced by Yager. Usually, such negations are generated point-by-point by functions defined on a set of probability values and called here negators. Recently it was shown that Yager negator plays a crucial role in the definition of pd-independent linear negators: any linear negator is a function of Yager negator. Here, we prove that the sequence of multiple negations of pd generated by a linear negator converges to the uniform distribution with maximal entropy. We show that any pd-independent negator is non-involutive, and any non-trivial linear negator is strictly contracting. Finally, we introduce an involutive negator in the class of pd-dependent negators that generates an involutive negation of probability distributions.

Keywords

Cite

@article{arxiv.2103.16176,
  title  = {Contracting and Involutive Negations of Probability Distributions},
  author = {Ildar Batyrshin},
  journal= {arXiv preprint arXiv:2103.16176},
  year   = {2021}
}

Comments

12 pages, 2 figures