Skip to main content

Research Repository

Advanced Search

Case-based methods and agent-based modelling: bridging the divide to leverage their combined strengths

Castellani, Brian; Barbrook-Johnson, Peter; Schimpf, Corey

Case-based methods and agent-based modelling: bridging the divide to leverage their combined strengths Thumbnail


Authors

Peter Barbrook-Johnson

Corey Schimpf



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.

Citation

Castellani, B., Barbrook-Johnson, P., & Schimpf, C. (2019). Case-based methods and agent-based modelling: bridging the divide to leverage their combined strengths. International Journal of Social Research Methodology, 22(4), 403-416. https://doi.org/10.1080/13645579.2018.1563972

Journal Article Type Article
Acceptance Date Dec 21, 2018
Online Publication Date Jan 16, 2019
Publication Date Jan 16, 2019
Deposit Date Feb 1, 2019
Publicly Available Date Mar 29, 2024
Journal International Journal of Social Research Methodology
Print ISSN 1364-5579
Electronic ISSN 1464-5300
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 22
Issue 4
Pages 403-416
DOI https://doi.org/10.1080/13645579.2018.1563972

Files





You might also like



Downloadable Citations