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Aggregation in system dynamics
Author(s) -
Rahn R. Joel
Publication year - 1985
Publication title -
system dynamics review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.491
H-Index - 57
eISSN - 1099-1727
pISSN - 0883-7066
DOI - 10.1002/sdr.4260010109
Subject(s) - computer science , statistical physics , system dynamics , dissipative system , analogy , physical system , stochastic modelling , complex system , work (physics) , dynamics (music) , mathematics , physics , artificial intelligence , linguistics , philosophy , statistics , quantum mechanics , acoustics , thermodynamics
Stochastic aspects of systems have generally been ignored in most system dynamics studies except for purposes of sensitivity testing. Yet any model that claims to be more than simply a phenomenological description of a system must treat the underlying stochasticity explicitly in terms of its contribution to the dynamics. Recent work in chemical, biological, and hydrodynamic systems has shown that the aggregation of stochastic effects can lead to novel behavior (self‐organization in dissipative systems). In this paper, an analogy between models of these physical systems and system dynamics models is developed, in which dynamic models are seen to be an approximation (to lowest order in an expansion in system size) to a stochastic model for the system. The theoretical results derived for the physical system models are evaluated for their application to system dynamics models. A research strategy to elaborate this approach to analyzing a more general class of systems is proposed.