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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This model is a replication of that described by Peterson (2002) and illustrates the ‘spread’ feedback loop type described in Millington (2013).
This model illustrates a positive ‘transport’ feedback loop in which lines with different resistance to flows of material result in variation in rates of change in linked entities.
This model illustrates a positive ‘growth’ feedback loop in which the areal extent of an entity increases through time.
This is a replication of the altruistic trait selection model described in Pepper & Smuts (2000, 2002).
This model extends the bounded confidence model of Deffuant and Weisbuch. It introduces online contexts in which a person can deliver his or her opinion to several other persons. There are 2 additional parameters accessibility and connectivity.
This is an agent-based model that allows to test alternative designs for three model components. The model was built using the LUDAS design strategy, while each alternative is in line with the strategy. Using the model, it can be shown that alternative designs, though built on the same strategy, lead to different land-use patterns over time.
How can species evolve a cooperative network to keep the environment suitable for life?
Agents are linked in a social-network and make decisions on which of 2 types of behavior to adopt. We explore consequences of different information feedback and providing targeted feedback to individuals.
This model explores the effects of agent interaction, information feedback, and adaptive learning in repeated auctions for farmland. It gathers information for three types of sealed-bid auctions, and one English auction and compares the auctions on the basis of several measures, including efficiency, price information revelation, and ability to handle repeated bidding and agent learning.
The model, presented here, is a re-implementation of the Pepper and Smuts’ model : - Pepper, J.W. and B.B. Smuts. 2000. “The evolution of cooperation in an ecological context: an agent-based model”. Pp. 45-76 in T.A. Kohler and G.J. Gumerman, eds. Dynamics of human and primate societies: agent-based modeling of social and spatial processes. Oxford University Press, Oxford. - Pepper, J.W. and B.B. Smuts. 2002. “Assortment through Environmental Feedback”. American Naturalist, 160: 205-213 […]
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