Nonlinearity in Social Service Evaluation: A Primer on Agent-based Modeling.
Measurement of nonlinearity in social service research and evaluation relies primarily on spatial analysis and, to a lesser extent, social network analysis. Recent advances in geographic methods and computing power, however, allow for the greater use of simulation methods. These advances now enable...
| Publicado en: | Social Work Research Vol. 35; no. 1; pp. 20 - 25 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
National Association of Social Workers
March 2011
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=508192093&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 508192093 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10705309 SWK jtl: Social Work Research issn: 10705309 maglogo: N pubinfo: dt: March 2011 vid: 35 iid: 1 pid: 271 pub: National Association of Social Workers artinfo: ui: 508192093 ppf: 20 ppct: 5 formats: fmt: – @attributes: type: T – @attributes: type: P size: 471KB tig: atl: Nonlinearity in Social Service Evaluation: A Primer on Agent-based Modeling. aug: au: Israel, Nathaniel Wolf-Branigin, Michael su: Research evaluation Multiagent systems Social services -- Research sug: subj: Research evaluation Multiagent systems Social services -- Research keyword: Agent-based modeling Research -- Methodology -- Computer programs ab: Measurement of nonlinearity in social service research and evaluation relies primarily on spatial analysis and, to a lesser extent, social network analysis. Recent advances in geographic methods and computing power, however, allow for the greater use of simulation methods. These advances now enable evaluators and researchers to simulate complex adaptive systems (CASs) by applying agent-based modeling (ABM). CASs reflect the interactions of competitive and cooperative tendencies found in agents. ABM simulations create and test generated observable patterns using the fewest number of plausible decision rules and agents. This primer presents essential concepts for understanding ABM as social service applications of complexity theory shift from a metaphorical perspective to a formalized evaluation method. Further developments in ABM methods need to focus on concepts emanating from the study of complexity science, including the concepts of the wisdom of groups, strengths found in diverse perspectives, robustness, interconnectedness, sustainability, and conflict and cooperation. Appropriate software programs for developing and testing agent-based models are provided. [PUBLICATION ABSTRACT]. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|