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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Aroused public opinion has led to public debates on social responsibility issues in food supply chains. This model based op opinion dynamics and the linkages between involved actors simulates the public debate leading to the transitions.
A model of attitudinal dynamics based on the cognitive mechanism of emotional coherence. The code is written in Java. For initialization an additional dataset is required.
This is an agent-based model of the implementation of the self-enforcing agreement in cooperative teams.
This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.
This is an adaptation and extension of Robert Axtell’s model (2013) of endogenous firms, in Python 3.4
This NetLogo model implements the Walk Away strategy in a spatial public goods game, where individuals have the ability to leave groups with insufficient levels of cooperation.
We build a computational model to investigate, in an evolutionary setting, a series of questions pertaining to happiness.
The modeling includes citizens, bounded into families; firms and governments; all of them interacting in markets for goods, labor and real estate. The model is spatial and dynamic.
It is NetLogo reconstruction of the original FORTRAN code of the classical M. Cohen, J. March, and J. Olsen “garbage can model” (GCM or CMO) of collective decision-making.
This adaptation of the Relative Agreement model of opinion dynamics (Deffuant et al. 2002) extends the Meadows and Cliff (2012) implementation of this model in a manner that explores the effect of the network structure among the agents.
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