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 model can be used to optimize intervention strategies for inspection services.
This is a simplified version of a Complex Model of Voter Turnout by Edmonds et al.(2014). It was developed to better understand the mechanisms at play on that complex model.
This is an agent-based model designed to explore the evolution of cooperation under changes in resources availability for a given population
This model simulate product diffusion on different social network structures.
An agent-based model of the Free/Libre Open Source Software (FLOSS) development process designed around agents selecting FLOSS projects to contribute to and/or download.
This model simulates the dynamics of eighteenth-century infantry battle tactics. The goal is to explore the effect of different tactics and individual traits in the dynamics of the combat.
The set of models test how receivers ability to accurately rank signalers under various ecological and behavioral contexts.
This model investigates how anti-conformist intentions could be related to some biases on the perception of attitudes. It starts from two case studies, related to the adoption of organic farming, that show anti-conformist intentions. It proposes an agent-based model which computes an intention based on the Theory of Reasoned Action and assumes some biases in the perception of others’ attitudes according to the Social Judgement Theory.
It investigates the conditions on the model parameter values for which the simulations reproduce the features observed in the case studies. The results suggest that perception biases are indeed likely to contribute to anti-conformist intentions.
The simulation generates two kinds of agents, whose proposals are generated accordingly to their selfish or selfless behaviour. Then, agents compete in order to increase their portfolio playing the ultimatum game with a random-stranger matching.
A haystack-style model of group selection to capture the essential features of colony foundation for queens of the ant based on observation of the ant Pogonomyrmex californicus.
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