Modeling and Predicting Self-Organization in Dynamic Systems out of Thermodynamic Equilibrium: Part 1: Attractor, Mechanism and Power Law Scaling
Year: 2024
Type: article
Abstract: Self-organization in complex systems is a process associated with reduced internal entropy and the emergence of structures that may enable the system to function more effectively in its environment and in a more competitive way with other states of the system or with other systems. This phenomenon typically occurs in the presence of energy gradients, facilitating energy transfer and entropy production. As a dynamic process, self-organization is best studied using dynamic measures and principles. The principles of minimizing unit action, entropy, and information while maximizing their total values are proposed as some of the dynamic variational principles guiding self-organization. Based on these principles, average action efficiency (AAE) is introduced as a potential quantitative measure of self-organization, reflecting the system’s efficiency as the ratio of events to total action per unit of time. Positive feedback loops link AAE to other system characteristics, potentially explaining power-law relationships and exponential growth patterns observed in complex systems. To explore this framework, we apply it to agent-based simulations of ants navigating between two locations on a 2D grid. The principles align with observed self-organization dynamics, and the results appear to support the model. By analyzing action efficiency, this study seeks to address fundamental questions about the nature of self-organization and system organization, such as "Why and how complex systems self-organize? What is organization and how organized is a system?". These findings suggest that the proposed models offer a useful perspective for understanding and potentially improving the design of complex systems.
Source: Processes
DOI: 10.3390/pr12122937
Authors: Matthew Brouillet, Georgi Y Georgiev
Institution: Worcester Polytechnic Institute
Language: English
Topic: Complex Systems and Dynamics
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,728
OpenAlex ID: W4405724797