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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The 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.
The purpose of this model is to examine equity and efficiency in crop production across a system of irrigated farms, as a function of maintenance costs, assessed water fees, and the capacity of farmers to trade water rights among themselves.
Three policy scenarios for urban expansion under the influences of the behaviours and decision modes of four agents and their interactions have been applied to predict the future development patterns of the Guangzhou metropolitan region.
This is the same model as used in the article ‘Modelling Society’s Evolutionary Forces’ except the Fertility graph has been corrected. The Fertility graph was not used in the published article.
This model is a small extension (rectangular layout) of Joshua Epstein’s (2001) model on development of thoughtless conformity in an artificial society of agents.
An agent-based model simulates emergence of in-group favoritism. Agents adopt friend selection strategies using an invariable tag and reputations meaning how cooperative others are to a group. The reputation can be seen as a kind of public opinion.
This multi-model (i.e. a model composed of interacting submodels) is a multi-level representation of a collective motion phenomenon. It was designed to study the impact of the mutual influences between individuals and groups in collective motion.
This generic individual-based model of a bird colony shows how the influence neighbour’s stress levels synchronize the laying date of neighbours and also of large colonies. The model has been used to demonstrate how this form of simulation model can be recognised as being ‘event-driven’, retaining a history in the patterns produced via simulated events and interactions.
A model of innovation diffusion in a structured population with two groups who are averse to adopting a produce popular with the outgroup.
In the context switching model, a society of agents embedded in multiple social relations, engages in a simple abstract game: the consensus game. Each agent has to choose towards one of two possible choices which are basically arbitrary. The objective of the game is to reach a global consensus, but the particular choice that gets collectively selected is irrelevant.
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