Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
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 feel free to 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 detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 10 of 117 results for "Marco Alberti" clear search
This model examines language dynamics within a social network using simulation techniques to represent the interplay of language adoption, social influence, economic incentives, and language policies. The agent-based model (ABM) focuses on interactions between agents endowed with specific linguistic attributes, who engage in communication based on predefined rules. A key feature of our model is the incorporation of network analysis, structuring agent relationships as a dynamic network and leveraging network metrics to capture the evolving inter-agent connections over time. This integrative approach provides nuanced insights into emergent behaviors and system dynamics, offering an analytical framework that extends beyond traditional modeling approaches. By combining agent-based modeling with network analysis, the model sheds light on the underlying mechanisms governing complex language systems and can be effectively paired with sociolinguistic observational data.
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.
Displaying 10 of 117 results for "Marco Alberti" clear search