Towards the Structure and Mechanisms of Complex Systems, the Approach of the Quantitative Theory of Meaning

TL;DR

This paper extends Shannon's Communication Theory to analyze complex systems by considering their topology and primary causes, proposing a new framework and the logistic Continuous Wavelet Transform for understanding their structure and dynamics.

Contribution

It introduces a novel approach to complex systems analysis based on a Quantitative Theory of Meaning, emphasizing topology and primary causes over effects.

Findings

Proposes the logistic Continuous Wavelet Transform (CWT) for system analysis.

Highlights the role of topology in system non-linearity and dynamics.

Lays groundwork for a new paradigm in complex systems research.

Abstract

We study analysis of complex systems using a Quantitative Theory of Meaning developed as an extention of Shannon's Communication Theory. The approach consideres complexity not in terms of the manifestation of its effects which are manifestation of the dynamics of the system, but in terms of primary causes and taking into account the topology of the system. Here, the dynamics of the system are provided by reflexive communication between heterogenious agents that make up the system. Unlike Shannon's Communication Theory the Theory of Meaning imposes restrictions on the complex systems being analyzed. Non-linearity and specific dynamics of the system arise as a consequence of the topology of the system. This topology also suggests a method for analyzing complex systems, the logistic Continuous Wavelet Transform (CWT). The paper also lays the foundation for future research in various fields studying complex systems of interacting geterogeneous agents, which may form a new paradigm for better understanding the structure, mechanisms, and dynamics of complex systems.