Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
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 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 additional 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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The simulation generates two kinds of agents, whose proposals are generated accordingly to their selfish or selfless behaviour. Then, agents compete in order to increase their portfolio playing the ultimatum game with a random-stranger matching.
We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.
This model is to simulate and compare the admission effects of 3 school matching mechanisms, serial dictatorship, Boston mechanism, and Chinese Parallel, under different settings of information released.
Endogenous social transition from a high-corruption state to a low-corruption state, replication of Hammond 2009
This is a social trust model for investigating the social relationships and social networks in the real world and in social media.
A simplified Arthur & Polak logic circuit model of combinatory technology build-out via incremental development. Only some inventions trigger radical effects, suggesting they depend on whole interdependent systems rather than specific innovations.
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.
We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.
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 the R code of the mathematical model that includes the decision making formulations for artificial agents. Plus, the code for graphical output is also added to the original code.
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