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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In 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.
Model of a very serious conflict about the relevance of a dam to impede its construction, between the client, the prime contractor, State, legalist opponents and activist opponents.
The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017). We aim at better explaining some patterns generated by this model, using a derived mathematical approximation of the evolution of the opinions averaged.
We consider agents having an opinion/esteem about each other and about themselves. During dyadic meetings, agents change their respective opinion about each other, and possibly about other agents they gossip about, with a noisy perception of the opinions of their interlocutor. Highly valued agents are more influential in such encounters.
We show that the inequality of reputations among agents have a negative effect on the opinions about the agents of low status.The mathematical analysis of the opinion dynamic shows that the lower the status of the agent, the more detrimental the interactions are for the opinions about this agent, especially when gossip is activated, while the interactions always tend to increase the opinions about agents of high status.
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 very simple model elaborated to explore what may happens when buyers (travelers) have more information than sellers (tourist destinations)
This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.
The 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
In our model, individual agents are distributed over a two-dimensional square lattice. The agents play the prisoner’s dilemma game with their neighbors, imitate the highest strategy, and then migrate to empty sites based on their tag preference.
ReSolEvo File output version
A general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners.
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