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 purpose of this agent-based model is to explore the emergent phenomena associated with scientific publication, including quantity and quality, from different academic types based on their publication strategies.
This model explores a social mechanism that links the reversal of the gender gap in education with changing patterns in relative divorce risks in 12 European countries.
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.
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.
This model is linked to the paper “The Epistemic Role of Diversity in Juries: An Agent-Based Model”. There are many version of this model, but the current version focuses on the role of diversity in whether juries reach correct verdicts. Using this agent-based model, we argue that diversity can play at least four importantly different roles in affecting jury verdicts. (1) Where different subgroups have access to different information, equal representation can strengthen epistemic jury success. (2) If one subgroup has access to particularly strong evidence, epistemic success may demand participation by that group. (3) Diversity can also reduce the redundancy of the information on which a jury focuses, which can have a positive impact. (4) Finally, and most surprisingly, we show that limiting communication between diverse groups in juries can favor epistemic success as well.
This is a computational model to articulate the theory and test some assumption and axioms for the trust model and its relationship to SBH.
Emulation is one of the simplest and most common mechanisms of social interaction. In this paper we introduce a descriptive computational model that attempts to capture the underlying dynamics of social processes led by emulation.
A logging agent builds roads based on the location of high-value hotspots, and cuts trees based on road access. A forest monitor sanctions the logger on observed infractions, reshaping the pattern of road development.
An agent-based model which explores Creativity and Urban Development
We built an agent-based model to foster the understanding of homeowners’ insulation activity.
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