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.
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This Agent-Based model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts.
This simulates the evolution of rules of shedding games based on cultural group selection. A number of groups play shedding games and evaluate the consequences on the average length and the difficulty
First version of the model “Neminem laedere. Socially damaging behaviours and how to contain them” by Domenico Parisi and Nicola Lettieri
This is version 1 of the Parental Investment Model by Aktipis & Fernandez-Duque.
A special case of the model ‘huntingforestry’, where a ‘pulsar’ pattern emerges, balancing hunting and game population growth.
This model is used to investigate the role of opinion leader. More specifically: the influence of ‘innovative behavior’, ‘weigth of normative influence’, ‘better product judgment’, ‘number of opinion
The model represents a team intended at designing a methodology for Institutional Planning. Included in ICAART’14 to exemplify how emotions can be identified in SocLab; and in ESSA’14 to show the Efficiency of Organizational Withdrawal vs Commitment.
This model describes a mechanism by which software agents can identify norms in an artificial agent society. In particular, this model uses a sequence mining approach to identify norms in an agent soc
3.8 with Unis
1.0
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