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 agent-based model examines the impact of seasonal aggregation, dispersion, and learning opportunities on the richness and evenness of artifact styles under random social learning (unbiased transmission).
We used a computer simulation to measure how well different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment.
This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.
This abstract model explores the emergence of altruistic behavior in networked societies. The model allows users to experiment with a number of population-level parameters to better understand what conditions contribute to the emergence of altruism.
The model is an experimental ground to study the impact of network structure on diffusion. It allows to construct a social network that already has some measurable level of homophily, and simulate a diffusion process over this social network.
This model describes and analyses the outcomes of the confrontation of interests, some conflicting, some common, about the management of a small river in SW France
The DITCH model has been developed to investigate partner selection processes, focusing on individual preferences, opportunities for contact, and group size to uncover how these may lead to differential rates of inter-ethnic marriage.
This is a complex “Data Integration Model”, following a “KIDS” rather than a “KISS” methodology - guided by the available evidence. It looks at the complex mix of social processes that may determine why people vote or not.
MERCURY aims to represent and explore two descriptive models of the functioning of the Roman trade system that aim to explain the observed strong differences in the wideness of distributions of Roman tableware.
Objective of our model is to simulate the emergence and operation of a technological niches (TN) in terms of actors’ interaction. A TN can be conceived as protected socio-economic space where radical innovations are developed and tested
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