Computational Model Library

MERCURY extension: population

Tom Brughmans | Published Thu May 23 06:28:44 2019

This model is an extended version of the original MERCURY model ( ) . It allows for experiments to be performed in which empirically informed population sizes of sites are included, that allow for the scaling of the number of tableware traders with the population of settlements, and for hypothesised production centres of four tablewares to be used in experiments.

Experiments performed with this population extension and substantive interpretations derived from them are published in:

Hanson, J.W. & T. Brughmans. In press. Settlement scale and economic networks in the Roman Empire, in T. Brughmans & A.I. Wilson (ed.) Simulating Roman Economies. Theories, Methods and Computational Models. Oxford: Oxford University Press.

A test-bed ecological model

Bruce Edmonds | Published Sun May 4 13:22:47 2014 | Last modified Wed May 15 14:18:58 2019

This is a multi-patch meta-population ecological model. It intended as a test-bed in which to test the impact of humans with different kinds of social structure.

Peer reviewed Modelling the Social Complexity of Reputation and Status Dynamics

André Grow Andreas Flache | Published Wed Feb 1 19:23:32 2017 | Last modified Wed Jan 23 16:46:42 2019

The purpose of this model is to illustrate the use of agent-based computational modelling in the study of the emergence of reputation and status beliefs in a population.

This model aims to understand the cumulative effects on the population’s vulnerability as represented by exposure to PM10 (particulate matter with diameter less than 10 micrometres) by different age and educational groups in two Seoul districts, Gangnam and Gwanak. Using this model, readers can explore individual’s daily commuting routine, and its health loss when the PM10 concentration of the current patch breaches the national limit of 100µg/m3.

Peer reviewed Ants Digging Networks

Elske van der Vaart | Published Fri Sep 14 13:21:46 2018

This is a NetLogo version of Buhl et al.’s (2005) model of self-organised digging activity in ant colonies. It was built for a master’s course on self-organisation and its intended use is still educational. The ants’ behavior can easily be changed by toggling switches on the interface, or, for more advanced students, there is R code included allowing the model to be run and analysed through RNetLogo.

This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.

MERCURY extension: transport-cost

Tom Brughmans | Published Mon Jul 23 11:08:11 2018

This is extended version of the MERCRUY model (Brughmans 2015) incorporates a ‘transport-cost’ variable, and is otherwise unchanged. This extended model is described in this publication: Brughmans, T., 2019. Evaluating the potential of computational modelling for informing debates on Roman economic integration, in: Verboven, K., Poblome, J. (Eds.), Structural Determinants in the Roman World.

Brughmans, T., 2015. MERCURY: an ABM of tableware trade in the Roman East. CoMSES Comput. Model Libr. URL

EthnoCultural Tag model (ECT)

David Hales Bruce Edmonds | Published Fri Oct 16 13:26:37 2015 | Last modified Wed May 9 10:04:58 2018

Captures interplay between fixed ethnic markers and culturally evolved tags in the evolution of cooperation and ethnocentrism. Agents evolve cultural tags, behavioural game strategies and in-group definitions. Ethnic markers are fixed.

We propose an agent-based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the bargaining model by Axtell, Epstein and Young.

We expose RA agent-based model of the opinion and tolerance dynamics in artificial societies. The formal mathematical model is based on the ideas of Social Influence, Social Judgment, and Social Identity theories.

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.