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 this model is to study the evolution of cooperation when agents are endowed with a limited set of receptors, a set of elementary actions and a neural network agents use to make decision
The model is used to study the conditions under which agents will cooperate in one-shot two-player Prisoner’s Dilemma games if they are able to withdraw from playing the game and can learn to recogniz
This is a NetLogo replication of the hill-climbing version of the Lansing-Kremer model of Balinese irrigation.
In the model agents make decisions to contribute of not to the public good of a group, and cooperators may punish, at a cost, defectors. The model is based on group selection, and is used to understan
The purpose of this model is to help understand how prehistoric societies adapted to the prehistoric American southwest landscape. In the American southwest there is a high degree of environmental var
This model simulates 2048 versions of shedding games and evaluates the consequences on the average length and the difficulty of the game agents experience. The purpose of the model is to understand th
This simulates the evolution of rules of shedding games based on cultural group selection. A number of groups play shedding games and evaluate the consequences on the average length and the difficulty
The model explores the possibility of the evolution of cooperation due to indirect reciprocity when agents derive information about the past behavior of the opponent in one-shot dilemma games.
This model describes the consequences of limited vision of agents in harvesting a common resource. We show the vulnerability of cooperation due to reduced visibility of the resource and other agents.
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.
Displaying 10 of 108 results for "Marco Alberti" clear search