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 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 includes different formulations how agents make decisions in irrigation games and this is compared with empirical data. The aim is to test different theoretical models, especially explaining effect of communication.
This is a social trust model for investigating the social relationships and social networks in the real world and in social media.
This model simulates different spread hypotheses proposed for the introduction of agriculture on the Iberian peninsula. We include three dispersal types: neighborhood, leapfrog, and ideal despotic distribution (IDD).
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.
Implementation of Milbrath’s (1965) model of political participation. Individual participation is determined by stimuli from the political environment, interpersonal interaction, as well as individual characteristics.
This is a short NetLogo example demonstrating how to initialize 500 agents with 4 correlated parameters each with random values by doing the necessary calculations in the program “R” and retrieving the results.
We provide an agent-based model of collective action, informed by Granovetter (1978) and its replication model by Siegel (2009). We use the model to examine the role of ICTs in collective action under different cultural and political contexts.
This model, realized on the NetLogo platform, compares utility levels at home and abroad to simulate agents’ migration and their eventual return. Our model is based on two fundamental individual features, i.e. risk aversion and initial expectation, which characterize the dynamics of different agents according to the evolution of their social contacts.
Model of shifting cultivation. All parameters can be controlled by the user or the model can be run in adaptive mode, in which agents innovate and select parameters.
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