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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A model on feeding and social interaction behaviour of pigs
Iris J.M.M. Boumans | Published Thursday, May 04, 2017 | Last modified Tuesday, February 27, 2018The model simulates interaction between internal physiological factors (e.g. energy balance) and external social factors (e.g. competition level) underlying feeding and social interaction behaviour of commercially group-housed pigs.
Agent-based model of WiFi tracking system in urban environment
Christopher Thron Khoi Tran | Published Friday, April 21, 2017This code simulates the WiFi user tracking system described in: Thron et al., “Design and Simulation of Sensor Networks for Tracking Wifi Users in Outdoor Urban Environments”. Testbenches used to create the figures in the paper are included.
TERRoir level Organic matter Interactions and Recycling model
Myriam Grillot | Published Wednesday, April 19, 2017 | Last modified Wednesday, June 17, 2020The TERROIR agent-based model was built for the multi-level analysis of biomass and nutrient flows within agro-sylvo-pastoral villages in West Africa. It explicitly takes into account both human organization and spatial extension of such flows.
05 CmLab V1.17 – Conservation of Money Laboratory
Garvin Boyle | Published Saturday, April 15, 2017In CmLab we explore the implications of the phenomenon of Conservation of Money in a modern economy. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.
Perceived Scientific Value and Impact Factor
Davide Secchi Stephen J Cowley | Published Wednesday, April 12, 2017 | Last modified Monday, January 29, 2018The model explores the impact of journal metrics (e.g., the notorious impact factor) on the perception that academics have of an article’s scientific value.
Peer reviewed MOOvPOP
Matthew Gompper Aniruddha Belsare Joshua J Millspaugh | Published Monday, April 10, 2017 | Last modified Saturday, April 19, 2025MOOvPOP 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, 2020MOOvPOPsurveillance 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.
The Effects of Fiscal Targets in a Currency Union: a Multi-Country Agent Based-Stock Flow Consistent Model
Ermanno Catullo Alessandro Caiani Mauro Gallegati | Published Saturday, March 11, 2017We present an Agent-Based Stock Flow Consistent Multi-Country model of a Currency Union to analyze the impact of changes in the fiscal regimes that is permanent changes in the deficit-to-GDP targets that governments commit to comply.
Managing ecological disturbances: Learning and the structure of social-ecological networks
Jacopo A. Baggio Vicken Hillis | Published Friday, March 03, 2017 | Last modified Thursday, August 02, 2018The aim of this model is to explore and understand the factors driving adoption of treatment strategies for ecological disturbances, considering payoff signals, learning strategies and social-ecological network structure
This is an agent-based model that simulates the structural evolution in food supply chain.
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