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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This is a simulation model of an intelligent agent that has the objective to learn sustainable management of a renewable resource, such as a fish stock.
BarterNet is a platform for modeling early barter networks with the aim of learning how supply and demand for a good determine if traders will learn to use that good as a form of money. Traders use a good as money when they offer to trade for it even if they can’t consume it, but believe that they can subsequently trade it for a good they can consume in the near future.
A model of attitudinal dynamics based on the cognitive mechanism of emotional coherence. The code is written in Java. For initialization an additional dataset is required.
The simulation model LAMDA investigates the influences of varying cognitive abilities of the decision maker on the truth-inducing effect of the Groves mechanism. Bounded rationality concepts are represented by information states and learning models.
The MOBILITY model analyzes how agents’ mobility affects the performance of social-ecological systems in different landscape configurations.
Risk assessments are designed to measure cumulative risk and promotive factors for delinquency and recidivism, and are used by criminal and juvenile justice systems to inform sanctions and interventions. Yet, these risk assessments tend to focus on individual risk and often fail to capture each individual’s environmental risk. This agent-based model (ABM) explores the interaction of individual and environmental risk on the youth. The ABM is based on an interactional theory of delinquency and moves beyond more traditional statistical approaches used to study delinquency that tend to rely on point-in-time measures, and to focus on exploring the dynamics and processes that evolve from interactions between agents (i.e., youths) and their environments. Our ABM simulates a youth’s day, where they spend time in schools, their neighborhoods, and families. The youth has proclivities for engaging in prosocial or antisocial behaviors, and their environments have likelihoods of presenting prosocial or antisocial opportunities.
The objective of the model is to evaluate the impact of seasonal forecasts on a farmer’s net agricultural income when their crop choices have different and variable costs and returns.
Demand planning requires processing of distributed information. In this process, individuals, their properties and interactions play a crucial role. This model is a computational testbed to investigate these aspects with respect to forecast accuracy.
Agent-based model using Blanche software 4.6.5. Blanche software is included in the dataset file.
This model simulates the dynamics of eighteenth-century infantry battle tactics. The goal is to explore the effect of different tactics and individual traits in the dynamics of the combat.
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