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.
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Opinions on contested energy infrastructures
Annalisa Stefanelli | Published Thursday, June 23, 2016This ABM simulates opinions on a topic (originally contested infrastructures) through the interactions between paired agents and based on the sociopsychological assumptions of social judgment theory (SJT; Sherif & Hovland, 1961).
Stylized agricultural land-use model for resilience exploration
Patrick Bitterman | Published Tuesday, June 14, 2016 | Last modified Monday, April 08, 2019This model is a highly stylized land use model in the Clear Creek Watershed in Eastern Iowa, designed to illustrate the construction of stability landscapes within resilience theory.
Agent-based simulation of small group decision-making under no communication
Christopher Poile | Published Thursday, May 26, 2016A 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.
Communication and social change in space and time
Sebastian Kluesener Francesco Scalone Martin Dribe | Published Tuesday, May 17, 2016 | Last modified Friday, October 13, 2017This agent-based model simulates the diffusion of a social change process stratified by social class in space and time which is solely driven social and spatial variation in communication links.
Endogenous dynamics of firms made up by networked agents: an exploratory analysis
Bernardo Alves Furtado Isaque Daniel Rocha Eberhardt | Published Wednesday, March 23, 2016 | Last modified Wednesday, October 05, 2016This is an adaptation and extension of Robert Axtell’s model (2013) of endogenous firms, in Python 3.4
Composite Collective Decision Making - ant colony foraging model
Tomer Czaczkes Benjamin I Czaczkes | Published Thursday, December 17, 2015The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.
STECCAR: a simulation of the diffusion of electric cars
A Kangur Lc Verbrugge W Jager M Bockarjova | Published Sunday, November 29, 2015In this Repast model the ‘Consumat’ cognitive framework is applied to an ABM of the Dutch car market. Different policy scenarios can be selected or created to examine their effect on the diffusion of EVs.
The purpose of this model is to enhance a basic ABM through a simple set of rules identified using the activity-driven models in order to produce more realistic patterns of pedestrian movement.
Citation Agents: A model of collective learning through scientific publication
Christopher Watts | Published Friday, July 31, 2015Simulates 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.
MedLanD Modeling Laboratory
C Michael Barton Sean Bergin Isaac Ullah Gary Mayer Hessam Sarjoughian Helena Mitasova | Published Friday, May 08, 2015 | Last modified Thursday, December 14, 2017The MML is a hybrid modeling environment that couples an agent-based model of small-holder agropastoral households and a cellular landscape evolution model that simulates changes in erosion/deposition, soils, and vegetation.
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