Title
State Aggregation and Population Dynamics in Linear Systems
Abstract
We consider complex systems that are composed of many interacting elements, evolving under some dynamics. We are interested in characterizing the ways in which these elements may be grouped into higher-level, macroscopic states in a way that is compatible with those dynamics. Such groupings may then be thought of as naturally emergent properties of the system. We formalize this idea and, in the case that the dynamics are linear, prove necessary and sufficient conditions for this to happen. In cases where there is an underlying symmetry among the components of the system, group theory may be used to provide a strong sufficient condition. These observations are illustrated with some artificial life examples.
Year
DOI
Venue
2005
10.1162/106454605774270624
Artificial Life
Keywords
Field
DocType
state aggregation,coarse-graining,linear systems,population dynamics,coarse graining,population dynamic,artificial life,emergent properties,group theory,linear system,complex system
Artificial life,Complex system,Population,Linear system,Computer science,Group theory,Artificial intelligence,Granularity
Journal
Volume
Issue
ISSN
11
4
1064-5462
Citations 
PageRank 
References 
7
1.02
6
Authors
3
Name
Order
Citations
PageRank
Jonathan E. Rowe145856.35
Michael D. Vose2752215.67
Alden H. Wright333045.58