Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
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 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 additional 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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This 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.
CHALMS simulates housing and land market interactions between housing consumers, developers, and farmers in a growing ex-urban area.
We provide a full description of the model following the ODD protocol (Grimm et al. 2010) in the attached document. The model is developed in NetLogo 5.0 (Wilenski 1999).
An agent based simulation of a political process based on stakeholder narratives
An ABM, derived from a case study and a series of surveys with greenhouse growers in the Westland, Netherlands. Experiments using this model showshow that the greenhouse horticulture industry displays diversity, adaptive complexity and an uneven distribution, which all suggest that the industry is an evolving system.
The purpose of this model is to investigate mechanisms driving the geography of educational inequality and the consequences of these mechanisms for individuals with varying attributes and mobility.
In this model agents meet, evaluate one another, decide whether or not to date, if and when to become sexual partners, and when to break up.
The agent based model matches origins and destinations using employment search methods at the individual level.
This model is intended to explore the effectiveness of different courses of interventions on an abstract population of infections. Illustrative findings highlight the importance of the mechanisms for variability and mutation on the effectiveness of different interventions.
Objective of our model is to simulate the emergence and operation of a technological niches (TN) in terms of actors’ interaction. A TN can be conceived as protected socio-economic space where radical innovations are developed and tested
Displaying 10 of 426 results agent-based model clear search