Computational Model Library

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.

Displaying 10 of 1180 results for "A Flache" clear search

We study cultural dissemination in the context of an Axelrod-like agent-based model describing the spread of cultural traits across a society, with an added element of social influence. This modification produces absorbing states exhibiting greater variation in number and size of distinct cultural regions compared to the original Axelrod model, and we identify the mechanism responsible for this amplification in heterogeneity. We develop several new metrics to quantitatively characterize the heterogeneity and geometric qualities of these absorbing states. Additionally, we examine the dynamical approach to absorbing states in both our Social Influence Model as well as the Axelrod Model, which not only yields interesting insights into the differences in behavior of the two models over time, but also provides a more comprehensive view into the behavior of Axelrod’s original model. The quantitative metrics introduced in this paper have broad potential applicability across a large variety of agent-based cultural dissemination models.

A simple model illustrating RA Fisher’s (1930) reconciliation of Darwinian selection with particulate genetic contributions.

ergodicity_test

Jakob Grazzini | Published Monday, November 29, 2010 | Last modified Saturday, April 27, 2013

This Python module contain a function that is able to test the ergodicity of a given agent based model. It is sufficient to produce one long time series and many smaller time series. The function uses

Tyche

Tony Lawson | Published Tuesday, February 28, 2012 | Last modified Saturday, April 27, 2013

Demographic microsimulation model used in speed tests against LIAM 2.

Feedback Loop Example: Vegetation Patch Growth

James Millington | Published Thursday, December 20, 2012 | Last modified Saturday, April 27, 2013

This model illustrates a positive ‘growth’ feedback loop in which the areal extent of an entity increases through time.

Societal Simulator v203 fertility graph fix

Tim Gooding | Published Wednesday, November 26, 2014

This is the same model as used in the article ‘Modelling Society’s Evolutionary Forces’ except the Fertility graph has been corrected. The Fertility graph was not used in the published article.

Multistate modeling extended by behavioral rules

Sabine Zinn Matthias Leuchter Anna Klabunde Frans Willekens | Published Wednesday, August 03, 2016 | Last modified Tuesday, March 13, 2018

Toolkit to specify demographic multistate model with a behavioural element linking intentions to behaviour

PoliSEA represents a continuous policy process cycle, integrated with the dynamics of a fishery social-ecological system. The policy process in the model is represented by interactions between policymakers and interest groups and subsequent voting during which policymaker decide to increase or decrease the fishing quota for the next season. Policymakers’ positions can be influenced by lobbying of interest groups or interest group coalitions. The quota adopted through the policy process determines the amount of fish that can be harvested from the fish population during the season.

NarcoLogic

Nicholas Magliocca | Published Thursday, August 29, 2019

Investigate spatial adaptive behaviors of narco-trafficking networks in response to various counterdrug interdiction strategies within the cocaine transit zone of Central America and associated maritime areas. Through the novel application of the ‘complex adaptive systems’ paradigm, we implement a potentially transformative coupled agent-based and interdiction optimization modeling approach to compellingly demonstrate: (a) how current efforts to disrupt narco-trafficking networks are in fact making them more widespread, resilient, and economically powerful; (b) the potential for alternative interdiction approaches to weaken and contain traffickers.

A spatio-temporal Agent Based Modeling (ABM) framework is developed to probabilistically predict farmers’ decisions in the context of climate-induced water scarcity under varying utility optimization functions. The proposed framework forecasts farmers’ behavior assuming varying utility functions. The framework allows decision makers to forecast the behavior of farmers through a user-friendly platform with clear output visualization. The functionality of the proposed ABM is illustrated in an agriculturally dominated plain along the Eastern Mediterranean coastline.

Study area GIS data available upon request to [email protected]

Displaying 10 of 1180 results for "A Flache" clear search

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