Computational Model Library

This model extends the original Artifical Anasazi (AA) model to include individual agents, who vary in age and sex, and are aggregated into households. This allows more realistic simulations of population dynamics within the Long House Valley of Arizona from AD 800 to 1350 than are possible in the original model. The parts of this model that are directly derived from the AA model are based on Janssen’s 1999 Netlogo implementation of the model; the code for all extensions and adaptations in the model described here (the Artificial Long House Valley (ALHV) model) have been written by the authors. The AA model included only ideal and homogeneous “individuals” who do not participate in the population processes (e.g., birth and death)–these processes were assumed to act on entire households only. The ALHV model incorporates actual individual agents and all demographic processes affect these individuals. Individuals are aggregated into households that participate in annual agricultural and demographic cycles. Thus, the ALHV model is a combination of individual processes (birth and death) and household-level processes (e.g., finding suitable agriculture plots).

As is the case for the AA model, the ALHV model makes use of detailed archaeological and paleoenvironmental data from the Long House Valley and the adjacent areas in Arizona. It also uses the same methods as the original model (from Janssen’s Netlogo implementation) to estimate annual maize productivity of various agricultural zones within the valley. These estimates are used to determine suitable locations for households and farms during each year of the simulation.

The model is a combination of a spatially explicit, stochastic, agent-based model for wild boars (Sus scrofa L.) and an epidemiological model for the Classical Swine Fever (CSF) virus infecting the wild boars.

The original model (Kramer-Schadt et al. 2009) was used to assess intrinsic (system immanent host-pathogen interaction and host life-history) and extrinsic (spatial extent and density) factors contributing to the long-term persistence of the disease and has further been used to assess the effects of intrinsic dynamics (Lange et al. 2012a) and indirect transmission (Lange et al. 2016) on the disease course. In an applied context, the model was used to test the efficiency of spatiotemporal vaccination regimes (Lange et al. 2012b) as well as the risk of disease spread in the country of Denmark (Alban et al. 2005).

References: See ODD model description.

This is a conceptual model of underlying forces creating industrial clusters. There are two contradictory forces - attraction and repulsion. Firms within the same Industry are attracted to each other and on the other hand, firms with the same Activity are repulsed from each other. In each round firm with the lowest fitness is selected to change its profile of Industries and Activities. Based on these simple rules interesting patterns emerge.

Bicycle encounter model

Gudrun Wallentin | Published Sat Oct 29 20:45:47 2016 | Last modified Fri Mar 29 19:38:22 2019

This Bicycle encounter model builds on the Salzburg Bicycle model (Wallentin & Loidl, 2015). It simulates cyclist flows and encounters, which are locations of potential accidents between cyclists.

LimnoSES - social-ecological lake management undergoing regime shifts

Romina Martin | Published Thu Nov 24 11:22:42 2016 | Last modified Fri Jan 18 12:59:12 2019

LimnoSES is a coupled system dynamics, agent-based model to simulate social-ecological feedbacks in shallow lake use and management.

Salzburg Bicycle model

Gudrun Wallentin | Published Sat Oct 29 19:38:25 2016

An ABM to simulate the spatio-temporal distribution of cyclists across the road network of the city of Salzburg.

A multithreaded PPHPC replication in Java

Nuno Fachada | Published Sat Oct 31 15:29:02 2015 | Last modified Tue Jan 19 16:13:02 2016

A multithreaded replication of the PPHPC model in Java for testing different ABM parallelization strategies.

Peer reviewed PPHPC - Predator-Prey for High-Performance Computing

Nuno Fachada | Published Sat Aug 8 16:27:27 2015 | Last modified Wed Nov 25 17:23:09 2015

PPHPC is a conceptual model for studying and evaluating implementation strategies for spatial agent-based models (SABMs). It is a realization of a predator-prey dynamic system, and captures important SABMs characteristics.

A consumer-demand simulation for Smart Metering tariffs (Innovation Diffusion)

Martin Rixin | Published Thu Aug 18 10:29:34 2011 | Last modified Sat Apr 27 20:18:17 2013

An Agent-based model simulates consumer demand for Smart Metering tariffs. It utilizes the Bass Diffusion Model and Rogers´s adopter categories. Integration of empirical census microdata enables a validated socio-economic background for each consumer.

Communication and social change in space and time

Sebastian Kluesener Francesco Scalone Martin Dribe | Published Tue May 17 10:30:29 2016 | Last modified Fri Oct 13 16:24:43 2017

This agent-based model simulates the diffusion of a social change process stratified by social class in space and time which is solely driven social and spatial variation in communication links.

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