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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FoxNet is an individual-based modelling framework that can be customised to generate high-resolution red fox Vulpes vulpes population models for both northern and southern hemispheres. FoxNet predicts red fox population dynamics, including responses to control and landscape productivity. Model landscapes (up to ~15,000 km^2 and bait layouts can be generated within FoxNet or imported as GIS layers.
If you use FoxNet, please cite:
Hradsky BA, Kelly L, Robley A, Wintle BA (in review). FoxNet: an individual-based modelling framework to support red fox management. Journal of Applied Ecology.
ACT is an ABM based on an existing conceptualisation of the concept of critical transitions applied to the energy transition. With the model we departed from the mean-field approach simulated relevant actor behaviour in the energy transition.
The purpose of this agent-based model is to compare different variants of crowdworking in a general way, so that the obtained results are independent of specific details of the crowdworking platform. It features many adjustable parameters that can be used to calibrate the model to empirical data, but also when not calibrated it yields essential results about crowdworking in general.
Agents compete for contracts on a virtual crowdworking platform. Each agent is defined by various properties like qualification and income expectation. Agents that are unable to turn a profit have a chance to quit the crowdworking platform and new crowdworkers can replace them. Thus the model has features of an evolutionary process, filtering out the ill suited agents, and generating a realistic distribution of agents from an initially random one. To simulate a stable system, the amount of contracts issued per day can be set constant, as well as the number of crowdworkers. If one is interested in a dynamically changing platform, the simulation can also be initialized in a way that increases or decreases the number of crowdworkers or number of contracts over time. Thus, a large variety of scenarios can be investigated.
This is the electronic companion to the paper “Modelling Electricity Consumption in Office Buildings: An Agent Based Approach”
Several taxonomies for empirical validation have been published. Our model integrates different methods to calibrate an innovation diffusion model, ranging from simple randomized input validation to complex calibration with the use of microdata.
This model is based on Joshua Epstein’s (2001) model on development of thoughtless conformity in an artificial society of agents.
MERCURY aims to represent and explore two descriptive models of the functioning of the Roman trade system that aim to explain the observed strong differences in the wideness of distributions of Roman tableware.
This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.
The model was built to study the links between consumer credit, wealth distribution and aggregate demand in a complex macroeconomics system.
In this model, we simulate the navigation behavior of homing pigeons. Specifically we use genetic algorithms to optimize the navigation and flocking parameters of pigeon agents.
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