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.
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Emulation is one of the simplest and most common mechanisms of social interaction. In this paper we introduce a descriptive computational model that attempts to capture the underlying dynamics of social processes led by emulation.
This model uses ’satisficing’ as a model for farmers’ decision making to learn about influences of alternative decision-making models on simulation results and to exemplify a way to transform a rather theoretical concept into a feasible decision-making model for agent-based farming models.
This model describes and analyses the Travel-Tour Case study.
The provided source code is the result of our efforts in replicating Epstein’s Demographic Prisoner’s Dilemma. The simulation model is written in Repast/J 3.1.
The purpose of Hegmon’s Sharing model is to develop an understanding of the effect sharing strategies have on household survival.
A general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners.
This MAS simulates the traffic of Barcelona Eixample. Uses a centralized AI system in order to control the traffic lights. Car agents are reactive and have no awareness of the intelligence of the system. They (try to) avoid collisions.
A reimplementation of the Wedding Ring model by Francesco Billari. We investigate partnership formation in an agent-based framework, and combine this with statistical demographic projections using real empirical data.
Agents co-operate or defect towards other agents in a prisoner’s dilemma, with strategy choice depending on whether agents share tags or are kin in different social structures.
This is a replication of the altruistic trait selection model described in Pepper & Smuts (2000, 2002).
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