About the CoMSES Model Library more info
CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model archive tutorial or contact us if you have any questions or concerns about archiving your model.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Peer reviewed BAM: The Bottom-up Adaptive Macroeconomics Model
Alejandro Platas López Alejandro Guerra-Hernández | Published Tue Jan 14 17:04:32 2020 | Last modified Sun Jul 26 00:26:21 2020Overview
Purpose
Modeling an economy with stable macro signals, that works as a benchmark for studying the effects of the agent activities, e.g. extortion, at the service of the elaboration of public policies..
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Peer reviewed Family Herd Demography
Abigail Buffington Andrew Yoak Ian M Hamilton Rebecca Garabed Mark Moritz | Published Mon Aug 15 19:41:24 2016 | Last modified Sat Jan 6 15:27:40 2018The model examines the dynamics of herd growth in African pastoral systems. We used it to examine the role of scale (herd size) stochasticity (in mortality, fertility, and offtake) on herd growth.
Exploring social psychology theory for modelling farmer decision-making
James Millington | Published Tue Sep 18 16:16:25 2012 | Last modified Sat Apr 27 20:18:32 2013To investigate the potential of using Social Psychology Theory in ABMs of natural resource use and show proof of concept, we present an exemplary agent-based modelling framework that explicitly represents multiple and hierarchical agent self-concepts