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 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.
We build a stylized model of a network of business angel investors and start-up entrepreneurs. Decisions are based on trust as a decision making tool under true uncertainty.
MoPAgrIB model simulates the movement of cultivated patches in a savannah vegetation mosaic ; how they move and relocate through the landscape, depending on farming practices, population growth, social rules and vegetation growth.
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.
This model uses ’satisficing’ as a model for farmers’ decision making to learn about influences of alternative decision-making models on simulation results and to exemplify a way to transform a rather theoretical concept into a feasible decision-making model for agent-based farming models.
This model describes and analyses the Travel-Tour Case study.
The provided source code is the result of our efforts in replicating Epstein’s Demographic Prisoner’s Dilemma. The simulation model is written in Repast/J 3.1.
The purpose of Hegmon’s Sharing model is to develop an understanding of the effect sharing strategies have on household survival.
This model introduces individual bias to the model of exploration and exploitation, simulates knowledge diffusion within organizations, aiming to investigate the effect of individual bias and other related factors on organizational objectivity.
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).
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