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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The CONSERVAT model evaluates the effect of social influence among farmers in the Lake Naivasha basin (Kenya) on the spatiotemporal diffusion pattern of soil conservation effort levels and the resulting reduction in lake sedimentation.
This multi-model (i.e. a model composed of interacting submodels) is a multi-level representation of a collective motion phenomenon. It was designed to study the impact of the mutual influences between individuals and groups in collective motion.
We used a computer simulation to measure how well different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment.
We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.
Endogenous social transition from a high-corruption state to a low-corruption state, replication of Hammond 2009
This abstract model explores the emergence of altruistic behavior in networked societies. The model allows users to experiment with a number of population-level parameters to better understand what conditions contribute to the emergence of altruism.
Simulates impacts of ants killing colony mates when in conflict with another nest. The murder rate is adjustable, and the environmental change is variable. The colonies employ social learning so knowledge diffusion proceeds if interactions occur.
Signaling chains are a special case of Lewis’ signaling games on networks. In a signaling chain, a sender tries to send a single unit of information to a receiver through a chain of players that do not share a common signaling system.
The model includes different formulations how agents make decisions in irrigation games and this is compared with empirical data. The aim is to test different theoretical models, especially explaining effect of communication.
A simulation model on planned recycling agent behavior (PRB_1.0) which creates a virtual district with different agent types, waste generation and collection processes.
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