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 model aims at simulating the car traffic. It allows to use either a macro or a micro sub-model for the simulation of the flow on the roads.
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.
A stylized scale model to codesign with villagers an agent-based model of bushmeat hunting in the periphery of Korup National Park (Cameroon)
This is the final version of the model. To simulate the normative dynamics we used the EmIL (EMergence In the Loop) Framework which was kindly provided by Ulf Lotzmann. http://cfpm.org/EMIL-D5.1.pdf
NetCommons simulates a social dilemma process in case of step-level public goods. Is possible to generate (or load from DL format) any different networks, to change initial parameters, to replicate a number of experimental situations, and to obtain a event history database in CSV format with information about the context of each agents’ decision, the individual behavior and the aggregate outcomes.
ForagerNet3_Demography is a non-spatial ABM for exploring hunter-gatherer demography. Key methods represent birth, death, and marriage. The dependency ratio is an imporant variable in many economic decisions embedded in the methods.
This ABM looks at the effect of multiple reviewers and their behavior on the quality and efficiency of peer review. It models a community of scientists who alternatively act as “author” or “reviewer” at each turn.
The model explores the emergence of inequality in cognitive and socio-emotional skills at the societal level within and across generations that results from differences in parental investment behavior during childhood and adolescence.
Comparing 7 alternative models of human behavior and assess their performance on a high resolution dataset based on individual behavior performance in laboratory experiments.
In this model, we simulate the navigation behavior of homing pigeons. Specifically we use genetic algorithms to optimize the navigation and flocking parameters of pigeon agents.
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