Evolutionary computation and agent-based modeling: biologically-inspired approaches for understanding complex social systems

Claudio Cioffi-Revilla (), Kenneth Jong and Jeffrey K. Bassett
Additional contact information
Claudio Cioffi-Revilla: Krasnow Institute for Advanced Study
Kenneth Jong: Krasnow Institute for Advanced Study
Jeffrey K. Bassett: Krasnow Institute for Advanced Study

Computational and Mathematical Organization Theory, 2012, vol. 18, issue 3, No 7, 356-373

Abstract: Abstract Computational social science in general, and social agent-based modeling (ABM) simulation in particular, are challenged by modeling and analyzing complex adaptive social systems with emergent properties that are hard to understand in terms of components, even when the organization of component agents is know. Evolutionary computation (EC) is a mature field that provides a bio-inspired approach and a suite of techniques that are applicable to and provide new insights on complex adaptive social systems. This paper demonstrates a combined EC-ABM approach illustrated through the RebeLand model of a simple but complete polity system. Results highlight tax rates and frequency of public issue that stress society as significant features in phase transitions between stable and unstable governance regimes. These initial results suggest further applications of EC to ABM in terms of multi-population models with heterogeneous agents, multi-objective optimization, dynamic environments, and evolving executable objects for modeling social change.

Keywords: Agent-based modeling; Social simulation; Evolutionary computation; MASON; RebeLand model (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10588-012-9129-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:comaot:v:18:y:2012:i:3:d:10.1007_s10588-012-9129-7

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10588

DOI: 10.1007/s10588-012-9129-7

Access Statistics for this article

Computational and Mathematical Organization Theory is currently edited by Terrill Frantz and Kathleen Carley

More articles in Computational and Mathematical Organization Theory from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().