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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Communication processes occur in complex dynamic systems impacted by person attitudes and beliefs, environmental affordances, interpersonal interactions and other variables that all change over time. Many of the current approaches utilized by Communication researchers are unable to consider the full complexity of communication systems or the over time nature of our data. We apply agent-based modeling to the Reinforcing Spirals Model and the Spiral of Silence to better elucidate the complex and dynamic nature of this process. Our preliminary results illustrate how environmental affordances (i.e. social media), closeness of the system and probability of outspokenness may impact how attitudes change over time. Additional analyses are also proposed.
This model converts cleaned up versions of .pgn files (records of real chess games) and conversts them into files that record all of the events and “possible” events within a game of chess. This is intended to be a way to create sets of data that capture event sequences within the relatively complex but finite context of chess games as a proxy or “toy” data set. Although not a perfect correlation, these toy data sets are a first step in analysing complex and dynamic systems of events and possible events that happen in the real world.
LimnoSES is a coupled system dynamics, agent-based model to simulate social-ecological feedbacks in shallow lake use and management.
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. This code corresponds to equations 1-70 given in the paper “A Mathematical Model of The Beer Game”.
The purpose of this model is to analyze the dynamics of endogenously created oscillations in housing prices using a system dynamics simulation model, built from the perspective of construction companies.
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.
This is the R code of the mathematical model used for verification. This code corresponds to equations 1-9, 15-53, 58-62, 69-70, and 72-75 given in the paper “A Mathematical Model of The Beer Game”.