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.

Evolution of Conditional Cooperation

Marco Janssen Miles Manning Oyita Udiani | Published Thu Aug 1 04:03:07 2013 | Last modified Fri May 13 22:07:23 2022

Cultural group selection model used to evaluate the conditions for agents to evolve who have other-regarding preferences in making decisions in public good games.

Effect of communication in irrigation games

Marco Janssen Jacopo Baggio | Published Wed Jan 14 04:08:32 2015 | Last modified Wed Aug 9 01:28:22 2017

The model includes different formulations how agents make decisions in irrigation games and this is compared with empirical data. The aim is to test different theoretical models, especially explaining effect of communication.

Heterogeneity of preferences and the dynamics of voluntary contributions to public goods

Engi Amin Amal Soliman Mohamed Abouelela | Published Thu Aug 18 19:24:09 2016 | Last modified Thu Jan 25 17:36:12 2018

This model simulates the heterogeneity of preferences in a PG game and how the interaction between them affects the dynamics of voluntary contributions. Model is based on the results of a human-based experiment.