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 model simulates a foraging system based on Middle Stone Age plant and shellfish foraging in South Africa.
We model the relationship between natural resource user“s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.
Model for evaluating various ambulance dispatching policies of an equity constrained emergency medical services under bounded rationality.
An agent-based framework that aggregates social network-level individual interactions to run targeting and rewarding programs for a freemium social app. Git source code in https://bitbucket.org/mchserrano/socialdynamicsfreemiumapps
The simulation model LAMDA investigates the influences of varying cognitive abilities of the decision maker on the truth-inducing effect of the Groves mechanism. Bounded rationality concepts are represented by information states and learning models.
A computational model of a classic small group study by Alex Bavelas. This computational model was designed to explore the difficulty in translating a seemingly simple real-world experiment into a computational model.
The simulation model SimPLS shows an application of the PLS agent concept, using SEM as empirical basis for the definition of agent architectures. The simulation model implements the PLS path model TAM about the decision of using innovative products.
This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.
We develop an agent-based model for collective behavior of routine medical check-ups, and specifically dental visits, in a social network.
It is NetLogo reconstruction of the original FORTRAN code of the classical M. Cohen, J. March, and J. Olsen “garbage can model” (GCM or CMO) of collective decision-making.
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