Computational Model Library

Due to the large extent of the Harz National Park, an accurate measurement of visitor numbers and their spatiotemporal distribution is not feasible. This model demonstrates the possibility to simulate the streams of visitors with ABM methodology.

MayaSim: An agent-based model of the ancient Maya social-ecological system

Scott Heckbert | Published Wed Jul 11 19:55:24 2012 | Last modified Tue Jul 2 17:14:49 2013

MayaSim is an agent-based, cellular automata and network model of the ancient Maya. Biophysical and anthropogenic processes interact to grow a complex social ecological system.

FLOSSSim: An Agent-Based Model of the Free/Libre Open Source Software (FLOSS) Development Process

Nicholas Radtke | Published Sat Dec 31 01:33:55 2011 | Last modified Sat Apr 27 20:18:32 2013

An agent-based model of the Free/Libre Open Source Software (FLOSS) development process designed around agents selecting FLOSS projects to contribute to and/or download.

This code simulates the WiFi user tracking system described in: Thron et al., “Design and Simulation of Sensor Networks for Tracking Wifi Users in Outdoor Urban Environments”. Testbenches used to create the figures in the paper are included.

Comparing agent-based models on experimental data of irrigation games

Jacopo Baggio Marco Janssen | Published Tue Jul 2 18:26:39 2013 | Last modified Wed Jul 3 17:22:09 2013

Comparing 7 alternative models of human behavior and assess their performance on a high resolution dataset based on individual behavior performance in laboratory experiments.

An agent-based framework that aggregates social network-level individual interactions to run targeting and rewarding programs for a freemium social app. Git source code in https://bitbucket.org/mchserrano/socialdynamicsfreemiumapps

9 Maturity levels in Empirical Validation - An innovation diffusion example

Martin Rixin | Published Wed Oct 19 13:42:28 2011 | Last modified Sat Apr 27 20:18:17 2013

Several taxonomies for empirical validation have been published. Our model integrates different methods to calibrate an innovation diffusion model, ranging from simple randomized input validation to complex calibration with the use of microdata.

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