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 1209 results for "Ian M Hamilton" clear search

A Model to Unravel the Complexity of Rural Food Security

Stefano Balbi Samantha Dobbie | Published Monday, August 22, 2016 | Last modified Sunday, December 02, 2018

An ABM to simulate the behaviour of households within a village and observe the emerging properties of the system in terms of food security. The model quantifies food availability, access, utilisation and stability.

The purpose of the AdaptPumpa model is to analyze the robustness of the Pumpa irrigation system in Nepal to climate change.

IDEAL

Arika Ligmann-Zielinska | Published Thursday, August 07, 2014

IDEAL: Agent-Based Model of Residential Land Use Change where the choice of new residential development in based on the Ideal-point decision rule.

Simulation of the Effects of Disorganization on Goals and Problem Solving

Dinuka Herath | Published Sunday, August 13, 2017 | Last modified Sunday, August 13, 2017

This is a model of the occurrence of disorganization and its impact on individual goal setting and problem-solving. This model therefore, explores the effects of disorganization on goal achievement.

Micro-level Adaptation, Macro-level Selection, and the Dynamics of Market Partitioning

César García-Díaz | Published Monday, October 19, 2015 | Last modified Monday, October 19, 2015

This model simulates the emergence of a dual market structure from firm-level interaction. Firms are profit-seeking, and demand is represented by a unimodal distribution of consumers along a set of taste positions.

IMine is a flexible framework which can be adopt multiple criteria for convergence to solve Influence Minig problems. It can use any diffusion model, as well as resilience to compute the influence of a set of nodes base on the use case.
The code is written and tested on ‘R’ v3.5

Simulation of the Governance of Complex Systems

Fabian Adelt Johannes Weyer Robin D Fink Andreas Ihrig | Published Monday, December 18, 2017 | Last modified Friday, March 02, 2018

Simulation-Framework to study the governance of complex, network-like sociotechnical systems by means of ABM. Agents’ behaviour is based on a sociological model of action. A set of basic governance mechanisms helps to conduct first experiments.

Land-Livelihood Transitions

Nicholas Magliocca Daniel G Brown Erle C Ellis | Published Monday, September 09, 2013 | Last modified Friday, September 13, 2013

Implemented as a virtual laboratory, this model explores transitions in land-use and livelihood decisions that emerge from changing local and global conditions.

ABWiSE

Liliana Perez jeffledge | Published Monday, December 20, 2021

The Agent-Based Wildfire Simulation Environment (ABWiSE) translates the concept of a moving fire front as a set of mobile fire agents that respond to, and interact with, vegetation, wind, and terrain. Presently, the purpose of ABWiSE is to explore how ABM, using simple interactions between agents and a simple atmospheric feedback model, can simulate emergent fire spread patterns.

Peer reviewed The Archaeological Sampling Experimental Laboratory (tASEL)

Isaac Ullah | Published Friday, March 11, 2022 | Last modified Wednesday, June 01, 2022

The Archaeological Sampling Experimental Laboratory (tASEL) is an interactive tool for setting up and conducting experiments about sampling strategies for archaeological excavation, survey, and prospection.

Displaying 10 of 1209 results for "Ian M Hamilton" clear search

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