A Practical Approach to Modeling Complex Adaptive Flows in Psychology and Social Science

Procedia Computer Science, 114, 165-174.

10 Pages Posted: 14 Nov 2017

See all articles by William P. Fisher

William P. Fisher

University of California, Berkeley - BEAR Center

Date Written: October 30, 2017

Abstract

Five moments in the formation and functioning of complex adaptive systems are:

(1) emergent regularities and patterns in the flow of matter, energy, and/or information;

(2) condensed schematic representations of these regularities enabling their identification;

(3) reproductively interchangeable variants of these representations serving as templates for new instances of the pattern;

(4) successful reproduction facilitated by the accuracy and reliability of the representations’ predictions of data flow regularities; and

(5) informational feedback that adaptively modifies and reorganizes representations to incorporate new variations in the data flow, cycling back the first moment.

These five moments are instantiated via stochastic models providing practical approaches to representing and managing complex adaptive psychological and social systems in education, health care, human resource management, etc. Local independence, unidimensionality, and statistical sufficiency criteria function as means of identifying, evaluating, and deploying conceptual and social forms of life acting as evolving agents in defined ecological niches. Bringing these agents into play systematically requires embodying them in technologies instrumental to making them readily recognizable and sharable across ecosystem niches. Modeling research and practice promoting sustainable and self-organizing ecosystems of this kind set the stage for redefining profit in terms of authentic wealth and value for life.

Keywords: complex adaptive systems, Rasch models, stochastic structures, invariance, mathematical models, self-organization, nonequilibrium dynamics

JEL Classification: C02

Suggested Citation

Fisher, William P., A Practical Approach to Modeling Complex Adaptive Flows in Psychology and Social Science (October 30, 2017). Procedia Computer Science, 114, 165-174. , Available at SSRN: https://ssrn.com/abstract=3069046

William P. Fisher (Contact Author)

University of California, Berkeley - BEAR Center ( email )

Berkeley, CA 94704
United States

HOME PAGE: http://www.LivingCapitalMetrics.com

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
28
Abstract Views
243
PlumX Metrics