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 10 of 221 results population clear search

Local scale mobility, namely foraging, leads to global population dispersal. Agents acquire information about their environment in two ways, one individual and one social. See also http://www.openabm.org/model/3846/

This agent-based model explores the existence of positive feedback loops related to illegal, unregulated, unreported (IUU) fishing; the use of forced labor; and the depletion of fish populations due to commercial fishing.

The Cardial Spread Model

Sean Bergin | Published Friday, September 29, 2017 | Last modified Monday, February 04, 2019

The purpose of this model is to provide a platform to test and compare four conceptual models have been proposed to explain the spread of the Impresso-Cardial Neolithic in the west Mediterranean.

The model employs an agent-based model for exploring the victim-centered approach to identifying human trafficking and the approach’s effectiveness in an abstract representation of migrant flows.

This generic model simulates climate change adaptation in the form of resistance, accommodation, and retreat in coastal regions vulnerable to sea level rise and flooding. It tracks how population changes as households retreat to higher ground.

Our societal belief systems are pruned by evolution, informing our unsustainable economies. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

Peer reviewed MOOvPOP

Matthew Gompper Aniruddha Belsare Joshua J Millspaugh | Published Monday, April 10, 2017 | Last modified Saturday, April 19, 2025

MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.

Peer reviewed MOOvPOPsurveillance

Matthew Gompper Aniruddha Belsare Joshua J Millspaugh | Published Tuesday, April 04, 2017 | Last modified Tuesday, May 12, 2020

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

Peer reviewed DogFoxCDVspillover

Aniruddha Belsare Matthew Gompper | Published Thursday, March 16, 2017 | Last modified Tuesday, April 04, 2017

The purpose of this model is to better understand the dynamics of a multihost pathogen in two host system comprising of high densities of domestic hosts and sympatric wildlife hosts susceptible to the pathogen.

A spatial model of resource-consumer dynamics

Arend Ligtenberg Guus Ten Broeke George Ak Van Voorn Jaap Molenaar | Published Wednesday, January 11, 2017 | Last modified Thursday, September 17, 2020

The model simulates agents in a spatial environment competing for a common resource that grows on patches. The resource is converted to energy, which is needed for performing actions and for surviving.

Displaying 10 of 221 results population clear search

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