About the CoMSES Model Library more info
Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models 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 publishing tutorial and contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with additional detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
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MedLanD Modeling Laboratory
C Michael Barton Sean Bergin Isaac Ullah Gary Mayer Hessam Sarjoughian Helena Mitasova | Published Friday, May 08, 2015 | Last modified Thursday, December 14, 2017The MML is a hybrid modeling environment that couples an agent-based model of small-holder agropastoral households and a cellular landscape evolution model that simulates changes in erosion/deposition, soils, and vegetation.
Multi-Agent Socio-Ecological Hani Terrace Model
Lei Dong Yunnan University | Published Saturday, March 29, 2025This model is to explore the changes of paddy field landscape and household livelihood structure in the village under different policy scenarios, evaluate the eco-social effects of different policies, and provide decision support tools for proposing effective and feasible policies.
Endogenous dynamics of firms made up by networked agents: an exploratory analysis
Bernardo Alves Furtado Isaque Daniel Rocha Eberhardt | Published Wednesday, March 23, 2016 | Last modified Wednesday, October 05, 2016This is an adaptation and extension of Robert Axtell’s model (2013) of endogenous firms, in Python 3.4
SimAdapt
François Rebaudo | Published Wednesday, August 29, 2012 | Last modified Monday, October 13, 2014SimAdapt: An individual-based genetic model for simulating landscape management impacts on populations
City Sandbox
Javier Sandoval | Published Thursday, January 09, 2020This model grows land use patterns that emerge as a result of land-use compatibilities stablished in urban development plans, land topography, and street networks. It contains urban brushes to paint streets and land uses as a way to learn about urban pattern emergence through free experimentation.
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