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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CRESY-I stands for CREativity from a SYstems perspetive, Model I. This is the base model in a series designed to describe a systems approach to creativity in terms of variation, selection and retention (VSR) subprocesses.
The set of models test how receivers ability to accurately rank signalers under various ecological and behavioral contexts.
This model employs optimal foraging theory principles to generate predictions of which coastal habitats are exploited in climatically stable versus variable environments, using the American Samoa as a study area.
This is a computational model to articulate the theory and test some assumption and axioms for the trust model and its relationship to SBH.
This is a very simple foraging model used to illustrate the features of Netlogo’s Profiler extension.
Demand planning requires processing of distributed information. In this process, individuals, their properties and interactions play a crucial role. This model is a computational testbed to investigate these aspects with respect to forecast accuracy.
A discrete-time stochastic model with state-dependent transmission probabilities and multi-agent simulations focusing on possible risks that could materialize in the final phase of the epidemic.
An empirically validated agent-based model of circular migration
This agent-based model using ‘Blanche’ software provides policy-makers with a simulation-based demonstration illustrating how autonomous agents network and operate complementary systems in a decentral
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).
Displaying 10 of 479 results for "Tim M Daw" clear search