Reasoning in Systems with Elements that Randomly Switch Characteristics

TL;DR

This paper investigates the stability of probability reasoning in complex systems where elements randomly switch characteristics, proposing modular models and analyzing their impact on system behavior and decision-making.

Contribution

It introduces a novel approach using sets with changing elements and modular forms to model systems with dynamic node properties.

Findings

Derived an expression for the mean dependence on switching probability

Analyzed system stability under element characteristic changes

Applied models to complex system queries and survey analysis

Abstract

We examine the issue of stability of probability in reasoning about complex systems with uncertainty in structure. Normally, propositions are viewed as probability functions on an abstract random graph where it is implicitly assumed that the nodes of the graph have stable properties. But what if some of the nodes change their characteristics? This is a situation that cannot be covered by abstractions of either static or dynamic sets when these changes take place at regular intervals. We propose the use of sets with elements that change, and modular forms are proposed to account for one type of such change. An expression for the dependence of the mean on the probability of the switching elements has been determined. The system is also analyzed from the perspective of decision between different hypotheses. Such sets are likely to be of use in complex system queries and in analysis of surveys.