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 norms that facilitate software citation, archival, interoperability, and reuse. 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.
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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The 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.
Model of shifting cultivation. All parameters can be controlled by the user or the model can be run in adaptive mode, in which agents innovate and select parameters.