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.
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.
This Agent-Based model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts.
Inspired by the SKIN model, the basic concept here is to model the acceptance and implementation of supplier innovations. This model includes three types of agents comprising suppliers, manufacturers and applicators.
This is the R code of the mathematical model used for verification. This code corresponds to equations 1-9, 15-53, 58-62, 69-70, and 72-75 given in the paper “A Mathematical Model of The Beer Game”.
Final project version - still needs a bit of work for being completly operational
This agent-based model examines the impact of seasonal aggregation, dispersion, and learning opportunities on the richness and evenness of artifact styles under random social learning (unbiased transmission).
Replication of the well known Artificial Anasazi model that simulates the population dynamics between 800 and 1350 in the Long House Valley in Arizona.