Model Library

This page features code snippets and models implementing a large range of phenomena key to Roman studies. These models can be reused and mashed up to create new models representing your own particular theories of ancient societies. Notice something is missing? Send us an email and we’ll add it!

Model Library

Centurions in the Roman legion

An agent-based model of Roman warfare exploring the role of Centurions in the Roman army. This model accompanies the following paper: Rubio-Campillo, Xavier, Pau Valdés Matías, and Eduard Ble. “Centurions in the Roman Legion: Computer Simulation and Complex Systems.” Journal of Interdisciplinary History 46, no. 2 (2015): 245–263. https://doi.org/10.1162/JINH_a_00833.

Authors: Xavier Rubio-Campillo, with Valdés Matías, P. and Ble, E.

Keywords: army, centurion, agent-based model

Language: C++

Citation: Rubio-Campillo, X.; Valdés Matías, P.; Ble, E. (2015) “Centurions in the Roman Legion: Computer Simulation and Complex Systems”, Journal of Interdisciplinary History 46:2: 245-263. Source code: https://github.com/xrubio/models/tree/master/centurionsRomanLegion

Demography dynamics and army recruitment in the Dutch limes

An agent-based model simulating the demographic development of the population along the Dutch Roman limes and the implications for army recruitment numbers. This model accompanies the following paper: Verhagen, Philip, Jamie Joyce, and Mark Groenhuizen. “Modelling the Dynamics of Demography in the Dutch Roman Limes Zone.” LAC 2014 Proceedings 0, no. 0 (2016): 13. https://doi.org/10.5463/lac.2014.62.

Authors: Verhagen P, J Joyce & M Groenhuijzen

Keywords: demography, population dynamics, army, limes

Language: Netlogo

Citation:  Verhagen P, J Joyce & M Groenhuijzen (2016) Batavian Demography and Army Recruitment. http://modelingcommons.org/browse/one_model/4678#model_tabs_browse_info
Verhagen, Philip, Jamie Joyce, and Mark Groenhuizen. “Modelling the Dynamics of Demography in the Dutch Roman Limes Zone.” LAC 2014 Proceedings 0, no. 0 (2016): 13. https://doi.org/10.5463/lac.2014.62.

License: CC BY-NC 4.0

MERCURY: an ABM of tableware trade in the Roman East

An agent-based model representing Temin’s Roman market economy theory and Bang’s Roman bazaar theory as social network structures, simulating their effects on tableware distribution. This model accompanies the following paper: Brughmans, Tom, and Jeroen Poblome. “Roman Bazaar or Market Economy? Explaining Tableware Distributions through Computational Modelling.” Antiquity 90, no. 350 (2016): 393–408. https://doi.org/10.15184/aqy.2016.35.

Authors: Tom Brughmans and Jeroen Poblome

Keywords: social networks, Roman economy, Agent-based model, integration, tableware, ceramics, trade, Eastern Mediterranean

Language: Netlogo

Citation: Brughmans, Tom, (2015, May 01). “MERCURY: an ABM of tableware trade in the Roman East” (Version 1.1.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/4347/releases/1.1.0/

License: CC BY-NC 4.0

MERCURY extension: transport-cost

This extended version of the MERCRUY model (Brughmans 2015) incorporates a ‘transport-cost’ variable, and is otherwise unchanged. It has been used to explore corrections between the cost of tableware products and the network distance away from their place of production. 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.

Authors: Tom Brughmans

Keywords: social networks, Roman economy, Agent-based model, integration, tableware, ceramics, trade, Eastern Mediterranean

Language: Netlogo

Citation: Brughmans, Tom (2018, July 23). “MERCURY extension: transport-cost” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/d67fd7ce-a6df-4d25-b10c-765b455b80f0/releases/1.0.0/

License: CC BY-NC 3.0

MERCURY extension: population

This model is an extended version of the original MERCURY model (Brughmans 2015). 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.

Authors: Tom Brughmans

Keywords: social networks, Roman economy, Agent-based model, integration, tableware, ceramics, trade, Eastern Mediterranean

Language: Netlogo

Citation: Brughmans, Tom (2019, May 23). “MERCURY extension: population” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/fbd47935-65d2-450b-8dd9-657471808a91/releases/1.0.0/

License: CC BY-NC 3.0

Network structures

A model with code to create different network structures: small-world, preferential attachment, circular, star, wheel, lattice, random, nearest neighbour.

Authors: Tom Brughmans.

Keywords: network, small world, preferential attachment, agent-based model.

Language: Netlogo

Brughmans, Tom (2018, October 02). “Network structures tutorial” (Version 1.3.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/5bf9334e-0886-4be3-84ea-849352a0319d/releases/1.3.0/

License: CC-BY-3.0

ORBIS: importing a Roman transport system

An agent-based model in Netlogo that allows for the ORBIS geospatial network model of the Roman world to be imported into Netlogo.

Authors: code and .graphml representation by Tom Brughmans. ORBIS data by Walter Scheidel, Elijah Meeks and Karl Grossner.

Keywords: ORBIS, transport, network, Roman economy, agent-based model, trade, connectivity.

Language: Netlogo

Citation: Brughmans, Tom (2018, September 30). “Importing a Roman transport network” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/92b5dc6c-a124-4647-91d4-e7365264eac8/releases/1.0.0/

License: CC-BY-3.0

Modeling the Roman Bazaar

An agent-based model representing Bang’s Roman Bazaar theory using social networks. This model accompanies the following paper: Graham, Shawn, and Scott Weingart. “The Equifinality of Archaeological Networks: An Agent Based Exploratory Lab Approach.” Journal of Archaeological Method and Theory 22 (2015): 248–274. https://doi.org/10.1007/s10816-014-9230-y.

Authors: Shawn Graham and Scott Weingart

Keywords: bazaar, Roman economy, social networks, bricks, Agent-based model

Language: Netlogo

Citation: Graham, Shawn and Weingart, Scott (2013): Modeling the Roman Bazaar. figshare. Code. https://doi.org/10.6084/m9.figshare.92953.v5

Robustness betweenness centrality

An agent-based model measures the development of the network measure of betweenness centrality of a selected node under the influence of randomly adding nodes and their associated connections to the network from a previously created dataset. This model accompanies the following paper:  Groenhuijzen, Mark R., and Philip Verhagen. “Testing the Robustness of Local Network Metrics in Research on Archeological Local Transport Networks.” Frontiers in Digital Humanities 3, no. 6 (2016): 1–14. https://doi.org/10.3389/fdigh.2016.00006.

Downloads:

Authors: Mark Groenhuizen and Philip Verhagen

Keywords: limes, networks, betweenness, sensitivity analysis, routes, transport system

Language: Netlogo

Citation: Groenhuijzen, Mark R., and Philip Verhagen. “Testing the Robustness of Local Network Metrics in Research on Archeological Local Transport Networks.” Frontiers in Digital Humanities 3, no. 6 (2016): 1–14. https://doi.org/10.3389/fdigh.2016.00006.

License: CC BY-NC 4.0

Sheep and cattle herd dynamics

An agent-based model investigating changes in pastoral production as a result of differing population dynamics of sheep and cattle herds subjected to different animal husbandry practices. This model accompanies the following paper: Joyce, Jamie, and Philip Verhagen. “Simulating the Farm: Computational Modelling of Cattle and Sheep Herd Dynamics for the Analysis of Past Animal Husbandry Practices.” LAC 2014 Proceedings 0, no. 0 (2016): 17. https://doi.org/10.5463/lac.2014.59.

Authors: Jamie Joyce and Philip Verhagen

Keywords: cattle, farming, sheep, animal husbandry, subsistence, Agent-based model

Language: Netlogo

Citation: Joyce, J. and Verhagen, P. (2016) Sheep&CattleHerdDynamics Model. http://modelingcommons.org/browse/one_model/4684#model_tabs_browse_info
Joyce, Jamie, and Philip Verhagen. “Simulating the Farm: Computational Modelling of Cattle and Sheep Herd Dynamics for the Analysis of Past Animal Husbandry Practices.” LAC 2014 Proceedings 0, no. 0 (2016): 17. https://doi.org/10.5463/lac.2014.59.

License: CC BY-NC 4.0

Social learning amphorae (Coto-Sarmiento et al.)

R code for performing principal component analysis, linear discriminant analysis and mantel test. Includes a dataset of 413 Dressel 20 amphorae from 5 workshops in Baetica. Data and code for the paper Coto-sarmiento, M., Rubio-campillo, X., Remesal, J., 2018. Identifying social learning between Roman amphorae workshops through morphometric similarity. J. Archaeol. Sci. 96, 117–123. doi:10.1016/j.jas.2018.06.002

Downloads:

Authors: Coto-Sarmiento and Rubio-Campillo

Keywords: amphorae, Dressel 20, ceramics, workshops

Language: R

Credits: Coto-Sarmiento (2018) LearningBaetica. Github repository with data and source code for the publication Coto-Sarmiento, M., Rubio-Campillo, X., Remesal, J. (2018): Identifying social learning between Roman amphorae workshops through morphometric similarity, Journal of Archaeological Science, 96, pp. 117–123, doi: https://doi.org/10.1016/j.jas.2018.06.002. https://github.com/Mcotsar/LearningBaetica

License: GPL-2, GPL-3

Spatial network models (Groenhuizen and Verhagen)

A range of spatial network creation models in Python applied to a set of 25 Roman sites in the Netherlands. These models accompany the following paper: Groenhuijzen, Mark R., and Philip Verhagen. “Comparing Network Construction Techniques in the Context of Local Transport Networks in the Dutch Part of the Roman Limes.” Journal of Archaeological Science: Reports 15 (2017): 235–51. https://doi.org/10.1016/j.jasrep.2017.07.024.

Spatial network models included in code:

  • Maximum distance networks
  • Proximal point networks
  • Gabriel graph
  • Efficiency networks (starting from minimum spanning tree)

Authors: Mark Groenhuizen and Philip Verhagen

Keywords: geographic, spatial, networks, python

Language: Python

Citation: Groenhuijzen, Mark R., and Philip Verhagen. “Comparing Network Construction Techniques in the Context of Local Transport Networks in the Dutch Part of the Roman Limes.” Journal of Archaeological Science: Reports 15 (2017): 235–51. https://doi.org/10.1016/j.jasrep.2017.07.024.

License: CC BY-NC 4.0