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 model is a modification of Metaphoria 2019, where the monetary system can be run with agents that do not die, but their characteristics are mutated as they are in the mortal population.
This repository contains the replication materials for the JASSS submission: ‘Indirect Reciprocity with Contagious Reputation in Large-Scale Small-World Networks’. Further detail on how to run the models is provided in README.txt.
The purpose of the model is to provide an analogy for how the Schwartz values may influence the aggregated economic performance, as measured by: public goods provision, private goods provision and leisure time.
This model is a market game for evaluating the effectiveness of the UK government’s 2008-2010 policy on promoting smart metering in the UK retail electricity market. We break down the policy into four
An agent-based model of species interaction on fragmented landscape is developed to address the question, how do population levels of predators and prey react with respect to changes in the patch connectivity as well as changes in the sharpness of threshold dispersal?
This model is a replication of that described by Peterson (2002) and illustrates the ‘spread’ feedback loop type described in Millington (2013).
The purpose of this model is to enhance a basic ABM through a simple set of rules identified using the activity-driven models in order to produce more realistic patterns of pedestrian movement.
MELBIS-V1 is a spatially explicit agent-based model that allows the geospatial simulation of the decision-making process of newcomers arriving in the bilingual cities and boroughs of the island of Montreal, Quebec in CANADA, and the resulting urban segregation spatial patterns. The model was implemented in NetLogo, using geospatial raster datasets of 120m spatial resolution.
MELBIS-V2 enhances MELBIS-V1 to implement and simulate the decision-making processes of incoming immigrants, and to analyze the resulting spatial patterns of segregation as immigrants arrive and settle in various cities in Canada. The arrival and segregation of immigrants is modeled with MELBIS-V2 and compared for three major Canadian immigration gateways, including the City of Toronto, Metro Vancouver, and the City of Calgary.
The School Enrollment Model is a spatially-explicit computational model that depicts a city, with schools and students located within the space. The model represents the Chilean school system, a market-based educational system, where people are free to choose among public, private voucher, or private fee-paying schools. In the model, students become aware of some schools, apply to schools, switch schools, pass or fail grade levels, and eventually either graduate or dropout. Schools select students, update their tuition, test scores, and other characteristics.
The purpose of the model is to represent the Chilean school system and analyze the different mechanisms that affected the enrollment distribution between public, private voucher, and private fee-paying school sectors during the period 2004-2016.
Agent-based modeling and simulation (ABMS) is a class of computational models for simulating the actions and interactions of autonomous agents with the goal of assessing their effects on a system as a whole. Several frameworks for generating parallel ABMS applications have been developed taking advantage of their common characteristics, but there is a lack of a general benchmark for comparing the performance of generated applications. We propose and design a benchmark that takes into consideration the most common characteristics of this type of applications and includes parameters for influencing their relevant performance aspects. We provide an initial implementation of the benchmark for RepastHPC one of the most popular parallel ABMS platforms, and we use it for comparing the applications generated by these platforms.
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