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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A simplified Arthur & Polak logic circuit model of combinatory technology build-out via incremental development. Only some inventions trigger radical effects, suggesting they depend on whole interdependent systems rather than specific innovations.
We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. Plus, the code for graphical output is also added to the original code.
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”.
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. This code corresponds to equations 1-70 given in the paper “A Mathematical Model of The Beer Game”.
This model employs optimal foraging theory principles to generate predictions of which coastal habitats are exploited in climatically stable versus variable environments, using the American Samoa as a study area.
This model represents technological and ecological behaviors of mobile hunter-gatherers, in a variable environment, as they produce, use, and discard chipped stone artifacts. The results can be analyzed and compared with archaeological sites.
chitwanabm is a spatially explicit agent-based model of population and land use in the Chitwan Valley, Nepal, designed to explore feedbacks between population and environment, with a heavy focus on community context and individual-level variation.
This is a multi-patch meta-population ecological model. It intended as a test-bed in which to test the impact of humans with different kinds of social structure.
Implementation of Milbrath’s (1965) model of political participation. Individual participation is determined by stimuli from the political environment, interpersonal interaction, as well as individual characteristics.
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