Case-Based Methods and Agent-Based Modelling: Bridging the Divide to Leverage Their Combined Strengths

Autor/inn/en	Castellani, Brian; Barbrook-Johnson, Peter; Schimpf, Corey
Titel	Case-Based Methods and Agent-Based Modelling: Bridging the Divide to Leverage Their Combined Strengths
Quelle	In: International Journal of Social Research Methodology, 22 (2019) 4, S.403-416 (14 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Castellani, Brian) ORCID (Barbrook-Johnson, Peter) ORCID (Schimpf, Corey)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1364-5579
DOI	10.1080/13645579.2018.1563972
Schlagwörter	Social Science Research; Systems Approach; Mixed Methods Research; Case Studies; Simulation + Suchen Sie Ihr Suchwort? Social scientific research; Sozialwissenschaftliche Forschung; Systemischer Ansatz; Case study; Fallstudie; Case Study; Simulation program; Simulationsprogramm
Abstract	Two leading camps for studying social complexity are case-based methods (CBM) and agent-based modelling (ABM). Despite the potential epistemological links between 'cases' and 'agents,' neither camp has leveraged their combined strengths. A bridge can be built, however, by drawing on Abbott's insight that 'agents are cases doing things', Byrne's suggestion that 'cases are complex systems with agency', and by viewing CBM and ABM within the broader trend towards computational modelling of cases. To demonstrate the utility of this bridge, we describe how CBM can utilise ABM to identify case-based trends; explore the interactions and collective behaviour of cases; and study different scenarios. We also describe how ABM can utilise CBM to identify agent types; construct agent behaviour rules; and link these to outcomes to calibrate and validate model results. To further demonstrate the bridge, we review a public health study that made initial steps in combining CBM and ABM. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01