Published In

International Journal of General Systems

Document Type

Post-Print

Publication Date

12-30-2020

Subjects

Reconstructability analysis, Machine learning, Agent-based simulation, Information theory, Sensitivity analysis, Wealth distribution model

Abstract

Reconstructability analysis, a methodology based on information theory and graph theory, was used to perform a sensitivity analysis of an agent-based model. The NetLogo BehaviorSpace tool was employed to do a full 2k factorial parameter sweep on Uri Wilensky’s Wealth Distribution NetLogo model, to which a Gini-coefficient convergence condition was added. The analysis identified the most influential predictors (parameters and their interactions) of the Gini coefficient wealth inequality outcome. Implications of this type of analysis for building and testing agent-based simulation models are discussed.

Description

This is the author’s version of a work that was accepted for publication in International Journal of General Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of General Systems

DOI

10.1080/03081079.2021.1874947

Persistent Identifier

https://archives.pdx.edu/ds/psu/34914

Available for download on Thursday, December 30, 2021

Share

COinS