Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
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 feel free to 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 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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This thesis presents an abstract spatial simulation model of the Maya Central Lowlands coupled human and natural system from 1000 BCE to the present day. It’s name is the Climatically Heightened but Anothropogenically Achieved Historical Kerplunk model (CHAAHK). The simulation features features virtual human groups, population centers, transit routes, local resources, and imported resources. Despite its embryonic state, the model demonstrates how certain anthropogenic characteristics of a landscape can interact with externally induced trauma and result in a prolonged period of relative sociopolitical uncomplexity. Analysis of batch simulation output suggests decreasing empirical uncertainties about ancient wetland modification warrants more investment. This first submission of CHAAHK’s code represents the simulation’s implementation that was featured in the author’s master’s thesis.
The purpose of the model is to simulate the spatial dynamics of potato late blight to analyse whether resistant varieties can be used effectively for sustainable disease control. The model represents an agricultural landscape with potato fields and data of a Dutch agricultural region is used as input for the model. We simulated potato production, disease spread and pathogen evolution during the growing season (April to September) for 36 years. Since late blight development and crop growth is weather dependent, measured weather data is used as model input. A susceptible and late blight resistant potato variety are distinguished. The resistant variety has a potentially lower yield but cannot get infected with the disease. However, during the growing season virulent spores can emerge as a result of mutations during spore production. This new virulent strain is able to infect the resistant fields, resulting in resistance breakdown. The model shows how disease severity, resistance durability and potato yield are affected by the fraction of fields across a landscape with a disease-resistant potato variety.
Model explains both the final state and the dynamics of the development process of the wine sector in the Małopolska region in Poland. Model admits heterogeneous agents (regular farms,large and small vineyards).
The purpose of this model is to provide a platform to test and compare four conceptual models have been proposed to explain the spread of the Impresso-Cardial Neolithic in the west Mediterranean.
The Mobility Model is a model of a small-scale fishery with the purpose to study the movement of fishers between different sub-regions within a larger region, as they move between different regions to fish.
This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.
MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.
The CHIME ABM explores information distribution networks and agents’ protective decision making in the context of hurricane landfall.
This model examines the potential impact of market collapse on the economy and demography of fishing households in the Logone Floodplain, Cameroon.
This model builds on another model in this library (“diffusion of culture”).
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