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 purpose of the model is to simulate the cultural hitchhiking hypothesis to explore how neutral cultural traits linked with advantageous traits spread together over time
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.
The model of market of one commodity , in which there are in each moment of time the same quantity and the same quantity of money was formulated and researched in this text. We also study this system as a game of automata.
This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.
This model simulates the lithic raw material use and provisioning behavior of a group that inhabits a permanent base camp, and uses stone tools.
Interactions of players embedded in a closed square lattice are determined by distance and overall gains and they lead to shifts of reward payoff between temptation and punishment. A new winner balancing against threats is ultimately discovered.
This is a very simple foraging model used to illustrate the features of Netlogo’s Profiler extension.
The simulation generates two kinds of agents, whose proposals are generated accordingly to their selfish or selfless behaviour. Then, agents compete in order to increase their portfolio playing the ultimatum game with a random-stranger matching.
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.
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