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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Using nodes from the 2002 General Social Survey sample, the code establishes a network of ties with a given homophily bias, and simulates Internet adoption rates in that network under three conditions: (i) no network externalities, (ii) general network externalities, where an individual’s reservation price is a function of the overall adoption rate in the network, (iii) specific network externalities, where reservation price is a function of the adoption rate in individual’s personal […]
Implemented as a virtual laboratory, this model explores transitions in land-use and livelihood decisions that emerge from changing local and global conditions.
The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.
Simulates the construction of scientific journal publications, including authors, references, contents and peer review. Also simulates collective learning on a fitness landscape. Described in: Watts, Christopher & Nigel Gilbert (forthcoming) “Does cumulative advantage affect collective learning in science? An agent-based simulation”, Scientometrics.
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.
A-KinGDom simulates the emergence of the social structure in a group of non-human primates. The model includes dominance and affiliative interactions which allow us to define four different attack and affiliative strategies.
This is a model of innovation implementation inside an organization. It characterizes an innovation as a set of distributed and technically interdependent tasks performed by a number of different and socially interconnected frontline workers.
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.
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.
The model simulates interactions in small, task focused groups that might lead to the emergence of status beliefs among group members.
Displaying 10 of 426 results agent-based model clear search