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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This is an agent-based model of a population of scientists alternatively authoring or reviewing manuscripts submitted to a scholarly journal for peer review. Peer-review evaluation can be either ‘confidential’, i.e. the identity of authors and reviewers is not disclosed, or ‘open’, i.e. authors’ identity is disclosed to reviewers. The quality of the submitted manuscripts vary according to their authors’ resources, which vary according to the number of publications. Reviewers can assess the assigned manuscript’s quality either reliably of unreliably according to varying behavioural assumptions, i.e. direct/indirect reciprocation of past outcome as authors, or deference towards higher-status authors.
This model is a replication of that described by Peterson (2002) and illustrates the ‘spread’ feedback loop type described in Millington (2013).
This model expands approaches from social practice theories and is used to investigate the ability of the underlying conceptual model to explain the emergence of social practices, defined as routine behaviour that is similar amoung peers.
The General Housing Model demonstrates a basic housing market with bank lending, renters, owners and landlords. This model was developed as a base to which students contributed additional functions during Arizona State University’s 2020 Winter School: Agent-Based Modeling of Social-Ecological Systems.
This ABM looks at the effect of multiple reviewers and their behavior on the quality and efficiency of peer review. It models a community of scientists who alternatively act as “author” or “reviewer” at each turn.
We use a threshold model to drive our simulated network analysis testing public support for candidates in invisible primaries. We assign voter thresholds for candidates and vary number of voters, attachment to candidates and decay. Results of the algorithm show effects of size of lead, attachment and size of decay.
This theoretical model includes forested polygons and three types of agents: forest landowners, foresters, and peer leaders. Agent rules and characteristics were parameterized from existing literature and an empirical survey of forest landowners.
This model was developed as part of a class project, and explores the population dynamics and spread of an invasive insect, Emerald Ash Borer, in a county.
This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.
A spatial prisoner’s dilemma model with mobile agents, de-coupled birth-death events, and harsh environments.
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