Computational Model Library

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.

Displaying 4 of 24 results calibration clear search

Comparing agent-based models on experimental data of irrigation games

Jacopo A. Baggio Marco Janssen | Published Tuesday, July 02, 2013 | Last modified Wednesday, July 03, 2013

Comparing 7 alternative models of human behavior and assess their performance on a high resolution dataset based on individual behavior performance in laboratory experiments.

MayaSim: An agent-based model of the ancient Maya social-ecological system

Scott Heckbert | Published Wednesday, July 11, 2012 | Last modified Tuesday, July 02, 2013

MayaSim is an agent-based, cellular automata and network model of the ancient Maya. Biophysical and anthropogenic processes interact to grow a complex social ecological system.

FLOSSSim: An Agent-Based Model of the Free/Libre Open Source Software (FLOSS) Development Process

Nicholas Radtke | Published Saturday, December 31, 2011 | Last modified Saturday, April 27, 2013

An agent-based model of the Free/Libre Open Source Software (FLOSS) development process designed around agents selecting FLOSS projects to contribute to and/or download.

9 Maturity levels in Empirical Validation - An innovation diffusion example

Martin Rixin | Published Wednesday, October 19, 2011 | Last modified Saturday, April 27, 2013

Several taxonomies for empirical validation have been published. Our model integrates different methods to calibrate an innovation diffusion model, ranging from simple randomized input validation to complex calibration with the use of microdata.

Displaying 4 of 24 results calibration clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept