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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Simplified representation of the model used to present the global model to farmers
SimAdapt: An individual-based genetic model for simulating landscape management impacts on populations
The purpose of the model is to explore the impacts of global change on the ability of a community of farmers to adapt their practices to an agricultural pest.
What is it?
This model demonstrates a very simple bidding market where buyers try to acquire a desired item at the best price in a competitive environment
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The purpose of the model is to simulate the future growth of human settlements in the Nile river valley in Egypt. The model contains processes to mimic spatial patterns found in the case study region.
This is a replication model of the matching problem including the mate search problem, which is the generalization of a traditional optimization problem.
Replication of the well known Artificial Anasazi model that simulates the population dynamics between 800 and 1350 in the Long House Valley in Arizona.
Knowledge Based Economy (KBE) is an artificial economy where firms placed in geographical space develop original knowledge, imitate one another and eventually recombine pieces of knowledge. In KBE, consumer value arises from the capability of certain pieces of knowledge to bridge between existing items (e.g., Steve Jobs illustrated the first smartphone explaining that you could make a call with it, but also listen to music and navigate the Internet). Since KBE includes a mechanism for the generation of value, it works without utility functions and does not need to model market exchanges.
This model describes and analyses the Travel-Tour Case study.
The objective of this study is to create a framework to simulate and analyze the effect of multiple business scenarios on the adoption behavior of a group of technology products.
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