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 logging agent builds roads based on the location of high-value hotspots, and cuts trees based on road access. A forest monitor sanctions the logger on observed infractions, reshaping the pattern of road development.
a computer-based role-playing game simulating the interactions between farming activities, livestock herding and wildlife in a virtual landscape reproducing local socioecological dynamics at the periphery of Hwange National Park (Zimbabwe).
This model was build to explore the bio-cultural interaction between AMH and Neanderthals during the Middle to Upper Paleolithic Transition in the Iberian Peninsula
We model the relationship between natural resource user´s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.
This is the electronic companion to the paper “Modelling Electricity Consumption in Office Buildings: An Agent Based Approach”
In this presentation, we use the concept of meme to explore evolution of demand.
This models simulates innovation diffusion curves and it tests the effects of the degree and the direction of social influences. This model replicates, extends and departs from classical percolation models.
This model is designed for the paper of “Bustle Changes the City - Facility for Stopping off and Modeling Urban Dynamics -“. And all experimental results in the paper were implemented in this model.
This model simulates the heterogeneity of preferences in a PG game and how the interaction between them affects the dynamics of voluntary contributions. Model is based on the results of a human-based experiment.
A dynamic model of social network formation on single-layer and multiplex networks with structural incentives that vary over time.
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