Paper Info
Title
A Macro-Level Order Metric for Self-Organizing Adaptive Systems
Abstract
Analyzing how agent interactions affect macro-level self-organized behaviors can yield a deeper understanding of how complex adaptive systems work. The dynamic nature of complex systems makes it difficult to determine if, or when, a system has reached a state of equilibrium or is about to undergo a major transition reflecting the appearance of self-organized states. Using the notion of local neighborhood entropy, this paper presents a metric for evaluating the macro-level order of a system. The metric is tested in two dissimilar complex adaptive systems with self-organizing properties: an autonomous swarm searching for multiple dynamic targets and Conway's Game of Life. In both domains, the proposed metric is able to graphically capture periods of increasing and decreasing self-organization (i.e. changes in macro-level order), equilibrium and points of criticality; displaying its general applicability in identifying these behaviors in complex adaptive systems.
Year
DOI
Venue
2018
10.1109/SASO.2018.00017
2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
Keywords
Field
DocType
self-organization,entropy,system order
Complex system,Level order,Swarm behaviour,Task analysis,Computer science,Adaptive system,Theoretical computer science,Criticality,Macro,Complex adaptive system,Distributed computing
Conference
ISSN
ISBN
Citations 
1949-3673
978-1-5386-5173-5
2
PageRank 
References 
Authors
0.39
0
2
Name
Order
Citations
PageRank
David King152.25
Gilbert L. Peterson225138.75