Computational Model Library

Linear Threshold

Kaushik Sarkar | Published Sat Nov 3 06:57:06 2012 | Last modified Sat Apr 27 20:18:37 2013

NetLogo implementation of Linear Threshold model of influence propagation.

Homophily and Distance Depending Network Generation for Modelling Opinion Dynamics

Sascha Holzhauer | Published Wed Aug 22 11:28:48 2012 | Last modified Tue Jun 18 10:50:05 2013

The model uses opinion dynamics to test a simple and ecient but empirically based approach for generating social networks in spatial agent-based models which explicitly takes into account restrictions and opportunities imposed by effects of baseline homophily and considers the probability of links that depends on geographical distance between potential partners.

Peer reviewed Axelrod_Cultural_Dissemination

Arezky Rodríguez | Published Wed Mar 27 15:36:22 2013 | Last modified Sun May 5 04:24:30 2013

The Axelrod’s model of cultural dissemination is an agent-model designed to investigate the dissemination of culture among interacting agents on a society.

MERCURY: an ABM of tableware trade in the Roman East

Tom Brughmans Jeroen Poblome | Published Thu Sep 25 14:50:21 2014 | Last modified Fri May 1 16:43:39 2015

MERCURY aims to represent and explore two descriptive models of the functioning of the Roman trade system that aim to explain the observed strong differences in the wideness of distributions of Roman tableware.

NetCommons

Francis Tseng | Published Wed May 18 20:57:27 2011 | Last modified Sat Apr 27 20:18:40 2013

NetCommons simulates a social dilemma process in case of step-level public goods. Is possible to generate (or load from DL format) any different networks, to change initial parameters, to replicate a number of experimental situations, and to obtain a event history database in CSV format with information about the context of each agents’ decision, the individual behavior and the aggregate outcomes.

An Agent-Based Model of Internet Diffusion Under General and Specific Network Externalities

Filiz Garip | Published Fri Apr 27 20:56:06 2012 | Last modified Sat Apr 27 20:18:23 2013

Using nodes from the 2002 General Social Survey sample, the code establishes a network of ties with a given homophily bias, and simulates Internet adoption rates in that network under three conditions: (i) no network externalities, (ii) general network externalities, where an individual’s reservation price is a function of the overall adoption rate in the network, (iii) specific network externalities, where reservation price is a function of the adoption rate in individual’s personal […]

Simulates the construction of scientific journal publications, including authors, references, contents and peer review. Also simulates collective learning on a fitness landscape. Described in: Watts, Christopher & Nigel Gilbert (forthcoming) “Does cumulative advantage affect collective learning in science? An agent-based simulation”, Scientometrics.

Social and Task Interdependencies in Innovation Implementation

Spiro Maroulis Uri Wilensky | Published Tue Jun 4 16:38:44 2013 | Last modified Tue Mar 4 19:47:22 2014

This is a model of innovation implementation inside an organization. It characterizes an innovation as a set of distributed and technically interdependent tasks performed by a number of different and socially interconnected frontline workers.

Modeling financial networks based on interpersonal trust

Anna Klabunde Michael Roos | Published Wed May 29 14:28:45 2013 | Last modified Thu Nov 28 12:31:40 2013

We build a stylized model of a network of business angel investors and start-up entrepreneurs. Decisions are based on trust as a decision making tool under true uncertainty.

Human mate choice is a complex system

Paul Smaldino Jeffrey C Schank | Published Fri Feb 8 19:17:22 2013 | Last modified Sat Apr 27 20:18:34 2013

A general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners.

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