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.
authors.affiliation: School of Computer Science, University of Birmingham, Birmingham B15 2TT, UK. J.E.Rowe@cs.bham.ac.uk
authors.forename: Jonathan E
authors.initials: JE
authors.lastname: Rowe
authors.forename: Michael D
authors.initials: MD
authors.lastname: Vose
authors.forename: Alden H
authors.initials: AH
authors.lastname: Wright
mesh_terms: D000818:Animals; D005075:Biological Evolution; D004247:DNA / Q000235:genetics; D016014:Linear Models; D008390:Markov Chains; D008566:Membranes / Q000378:metabolism; D008954:Models, Biological; D008962:Models, Theoretical; D009154:Mutation; D011157:Population Dynamics
chemical_list: D004247:DNA