About the CoMSES Model Library more info
Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
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 feel free to 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 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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FNNR-ABM
Judy Mak | Published Thursday, February 28, 2019 | Last modified Saturday, December 07, 2019FNNR-ABM is an agent-based model that simulates human activity, Guizhou snub-nosed monkey movement, and GTGP-enrolled land parcel conversion in the Fanjingshan National Nature Reserve in Guizhou, China.
Quick-start guide:
1. Install Python and set environmental path variables.
2. Install the mesa, matplotlib (optional), and pyshp (optional) Python libraries.
3. Configure fnnr_config_file.py.
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This is an agent-based model that simulates the structural evolution in food supply chain.
A model of urban expansion policy scenarios using an agent-based approach—a case of the Guangzhou Metropolitan Region of China
Guangjin Tian | Published Friday, March 21, 2014Three policy scenarios for urban expansion under the influences of the behaviours and decision modes of four agents and their interactions have been applied to predict the future development patterns of the Guangzhou metropolitan region.
Simulating the Cinema Market: How Cross-Cultural Differences in Social Influence Explain Box Office Distributions
Sebastiano Delre | Published Thursday, February 11, 2010 | Last modified Saturday, April 27, 2013This model simulates the motion picture industry and tests how social influences affect market shares. It is empirically validated at the micro level by a cross-cultural survey.
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