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.
A global model of the 1918-19 Influenza Pandemic. It can be run to match history or explore counterfactual questions about the influence of World War I on the dynamics of the epidemic. Explores two theories of the location of the initial infection.
The TechNet_04 is an abstract model that embeds a simple cultural tranmission process in an environment where interaction is structured by spatially-situated networks.
This model simulates the spread of anti-vaccine sentiments in cyber and physical space and how it creates emergence of clusters of anti-vacciners, which eventually lead to higher probablity of disease outbreaks.
the model can be used to describe the product diffusion in an Advance Selling Strategy. this model takes into account the consumers product adoption, and describe consumer’s online behavior based on four states.
The model presented here was created as part of my dissertation. It aims to study the impacts of topography and climate change on prehistoric networks, with a focus on the Magdalenian, which is dated to between 20 and 14,000 years ago.
This model simulates diffusion curves and it allows to test how social influence, network structure and consumer heterogeneity affect their spreads and their speeds.
We demonstrate how a simple model of community associated Methicillin-resistant Staphylococcus aureus (CA-MRSA) can be easily constructed by leveraging the statecharts and ReLogo capabilities in Repast Simphony.
This is the replication of the experiment performed by Eerkens and Lipo (2005) to look at the effect of copying errors when specific traits are transferred from an individual to another.