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 model simulates the mechanisms of evolution, or how allele frequencies change in a population over time.
This is an agent-based model with two types of agents: customers and insurers. Insurers are price-takers who choose how much to spend on their service quality, and customers evaluate insurers based on premium, brand preference, and their perceived service quality. Customers are also connected in a small-world network and may share their opinions with their network.
The ABM contains two types of agents: insurers and customers. These act within the environment of a motor insurance market. At each simulation, the model undergoes the following steps:
This agent-based model using ‘Blanche’ software provides policy-makers with a simulation-based demonstration illustrating how autonomous agents network and operate complementary systems in a decentral
This model simulates a simple aquatic ecosystem containing fish and food. It explores how individual interactions such as movement, feeding, and reproduction shape the population dynamics of fish over time.
CoDMER v. 2.0 was parameterized with ethnographic data from organizations dealing with prescribed fire and seeding native plants, to advance theory on how collective decisions emerge in ecological restoration.
Purpose of the model is to perform a “virtual experiment” to test the predator satiation hypothesis, advanced in literature to explain the mast seeding phenomenon.
Logônia is a NetLogo model that simulates the growth response of a fictional plant, Logônia, under different climatic conditions. The model uses climate data from WorldClim 2.1 (Fick & Hijmans, 2017) and demonstrates how to integrate the LogoClim model through the LevelSpace extension.
The model was developed according to the FAIR principles for research software (Barker et al., 2022) and is openly available on the CoMSES Network and GitHub.
How do households alter their spending patterns when they experience changes in income? This model answers this question using a random assignment scheme where spending patterns are copied from a household in the new income bracket.
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 illustrates how the effective population size and the rate of change in mean skill level of a cultural trait are affected by the presence of natural selection and/or the cultural transmission mechanism by which it is passed.
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