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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This is model that simulates how multiple kinds of peer effects shape the diffusion of innovations through different types of social relationships.
MIOvPOPsurveillance is set up to simulate harvest-based chronic wasting disease (CWD) surveillance of white-tailed deer (Odocoileus virginianus) populations in select Michigan Counties. New regions can be readily added, also the model can be readily adapted for other disease systems and used for informed-decision making during planning and implementation stages of disease surveillance in wildlife and free-ranging species.
The Episim framework builds upon the established transportation simulation MATSim and is capable of tracking agents’ movements within a network and thus computing infection chains. Several characteristics of the virus and the environment can be parametred, whilst the infection dynamics is computed based upon a compartment model. The spread of the virus can be mitigated by restricting the agents’ activity in certain places.
This is a tool to explore the effects of groupsĀ“ spatial segregation on the emergence of opinion polarization. It embeds two opinion formation models: a model of negative (and positive) social influence and a model of persuasive argument exchange.
This model allows for the investigation of the effect spatial clustering of raw material sources has on the outcome of the neutral model of stone raw material procurement by Brantingham (2003).
We introduce a model of prediction markets that uses opinion dynamics as its underlying mechanism for price formation. We base the opinion dynamics on the Deffuant model of bounded rationality. We have used this model to show that price formation in prediction markets can be robustly explained by opinion dynamics, and that the model can also explain phase transitions depending on just two parameters.
The model provides instruments for the simulation of interbank network evolution. There are tools for dynamic network analysis, allowing to evaluate graph topological invariants, thermodynamic network features and combinational node-based features.
This is a computational model to articulate the theory and test some assumption and axioms for the trust model and its relationship to SBH.
Designed to capture the evolutionary forces of global society.
This model simulates the heterogeneity of preferences in a PG game and how the interaction between them affects the dynamics of voluntary contributions. Model is based on the results of a human-based experiment.
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