Brughmans, T. (2020). Evaluating the potential of computational modelling for informing debates on Roman economic integration. In K. Verboven (Ed.), Complexity Economics. Building a New Approach to Ancient Economic History. Palgrave Studies in Ancient Economies (pp. 105–123). Palgrave Macmillan.

Brughmans, T. (2022). Why simulate Roman economies? In T. Brughmans & A. I. Wilson (Eds.), Simulating Roman Economies. Theories, Methods and Computational Models (pp. 3–36). Oxford University Press.

Brughmans, T., & Pecci, A. (2020). An inconvenient truth. Evaluating the impact of amphora reuse through computational simulation modelling. In C. Duckworth & A. Wilson (Eds.), Recycling and reuse in the Roman economy. Oxford studies on the Roman economy (pp. 191–234). Oxford University Press.

Brughmans, T., & Poblome, J. (2016). MERCURY: an agent-based model of tableware trade in the Roman East. Journal of Artificial Societies and Social Simulation, 19(1), http://jasss.soc.surrey.ac.uk/19/1/3.html.

Brughmans, T., & Poblome, J. (2017). The case for computational modelling of the Roman economy: a reply to Van Oyen. Antiquity, 91(359), 1364–1366. https://doi.org/10.15184/aqy.2017.166

Brughmans, T., & Poblome, J. (2016). Roman bazaar or market economy? Explaining tableware distributions through computational modelling. Antiquity, 90(350), 393–408. https://doi.org/10.15184/aqy.2016.35

Brughmans, T., & Wilson, A. I. (2022). Simulating Roman economies. Theories, methods and computational models. Oxford Studies on the Roman Economy. Oxford University Press.

Carrignon, S., Brughmans, T., & Romanowska, I. (2020). Tableware trade in the Roman East: Exploring cultural and economic transmission with agent-based modelling and approximate Bayesian computation. PLOS ONE, 15(11), e0240414. https://doi.org/10.1371/journal.pone.0240414

Carrignon, S., Brughmans, T., & Romanowska, I. (2022). Copying of economic strategies in eastern Mediterranean inter-regional tableware trade. In T. Brughmans & A. Wilson (Eds.), Simulating Roman Economies. Theories, Methods and Computational Models (pp. 144–166). Oxford University Press.

Conrad Djurdjevac, N., Daniel, C., Ana, F., Martin, H., Wolfram, P., Brigitta, S., Christof, S., Marcus, S., Niklas, W., & Johannes, W. (2018). Mathematical Modeling of the Spreading of Innovations in the Ancient World. ETopoi. Jouranl for Ancient Studies, 7, 1–32. https://doi.org/10.17171/4-7-1

Conrad Djurdjevac, N., Helfmann, L., Zonker, J., Winkelmann, S., & Schütte, C. (2018). Human mobility and innovation spreading in ancient times: a stochastic agent-based simulation approach. EPJ Data Science, 7(24). https://doi.org/10.1140/epjds/s13688-018-0153-9

Coto-sarmiento, M., Rubio-campillo, X., & Remesal, J. (2018). Identifying social learning between Roman amphorae workshops through morphometric similarity. Journal of Archaeological Science, 96(April), 117–123. https://doi.org/10.1016/j.jas.2018.06.002

Crabtree, S. (2016). Simulating Littoral Trade: Modeling the Trade of Wine in the Bronze to Iron Age Transition in Southern France. Land, 5(1), 5. https://doi.org/10.3390/land5010005

Fousek, J., Výtvarová, E., Mertel, A., Chalupa, A., & Hladká, E. (2016). Agent-Based Modelling And Simulation For The Geospatial Network Model Of The Roman World. International Symposium on Grids and Clouds (ISGC) 2016.

Fousek, J., Kaše, V., Mertel, A., Výtvarová, E., & Chalupa, A. (2018). Spatial constraints on the diffusion of religious innovations: The case of early Christianity in the Roman Empire. PLOS ONE, 13(12), e0208744. https://doi.org/10.1371/journal.pone.0208744

Graham, S. (2006). Networks, Agent-Based Models and the Antonine Itineraries: Implications for Roman Archaeology. Journal of Mediterranean Archaeology, 19(1), 45–64. https://doi.org/10.1558/jmea.2006.19.1.45

Graham, S., & Weingart, S. (2015). The Equifinality of Archaeological Networks: An Agent Based Exploratory Lab Approach. Journal of Archaeological Method and Theory, 22, 248–274. https://doi.org/10.1007/s10816-014-9230-y

Graham, S., Brughmans, T., & Romanowska, I. (2022). On Building FORVM: Making Our Research On The Roman Economy Playable...and Fun. In G. McKee & D. Wolin (Eds.), Re-Rolling the Past: Representations and Reinterpretations of Antiquity in Analog and Digital Games. ISAW Papers 22.3. https://hdl.handle.net/2333.1/ncjsxxs1

Groenhuijzen, M. R., & Verhagen, P. (2017). 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, 235–251. https://doi.org/10.1016/j.jasrep.2017.07.024

Groenhuijzen, M. R., & Verhagen, P. (2016). Testing the Robustness of Local Network Metrics in Research on Archeological Local Transport Networks. Frontiers in Digital Humanities, 3(6), 1–14. https://doi.org/10.3389/fdigh.2016.00006

Hanson, J. W., & Brughmans, T. (2022). Settlement scale and economic networks in the Roman Empire. In T. Brughmans & A. I. Wilson (Eds.), Simulating Roman Economies. Theories, Methods and Computational Models (pp. 109–143). Oxford University Press.

Joyce, J., & Verhagen, P. (2016). Simulating the Farm: Computational Modelling of Cattle and Sheep Herd Dynamics for the Analysis of Past Animal Husbandry Practices. LAC 2014 Proceedings, 0(0), 17. https://doi.org/10.5463/lac.2014.59

Kanters, H., Brughmans, T., & Romanowska, I. (2021). Sensitivity analysis in archaeological simulation: An application to the MERCURY model. Journal of Archaeological Science: Reports, 38(April), 102974. https://doi.org/10.1016/j.jasrep.2021.102974

Komoróczy, B., & Vlach, M. (2015). Simulating archeological models: Perspectives in protohistory. In S. Sázelová, M. Novák, & A. Mizerová (Eds.), Forgotten times and spaces: New perspectives in paleoanthropological, paleoetnological and archeological studies. 1st Edition. (pp. 494–506). nstitute of Archeology of the Czech Academy of Sciences; Masaryk University. https://doi.org/10.5817/CZ.MUNI.M210

Romanowska, I., Brughmans, T., Bes, P., Carrignon, S., Egelund, L., Lichtenberger, A., & Raja, R. (2021). A Study of the Centuries-Long Reliance on Local Ceramics in Jerash Through Full Quantification and Simulation. Journal of Archaeological Method and Theory. https://doi.org/10.1007/s10816-021-09510-0

Rubio-Campillo, X., Matías, P. V., & Ble, E. (2015). Centurions in the Roman Legion: Computer Simulation and Complex Systems. Journal of Interdisciplinary History, 46(2), 245–263. https://doi.org/10.1162/JINH_a_00833

Saller, R. P. (1994). Patriarchy, property, and death in the Roman family. Cambridge University Press.

Scheuermann, L. (2020). Simulation als Methode für die Altertumswissenschaften. Digital Classics Online, Bd. 5, 43-52 Seiten. https://doi.org/10.11588/DCO.2019.2.68127

Snyder, J. R., Dilaver, O., Stephenson, L. C., Mackie, J. E., & Smith, S. D. (2018). Agent-based modelling and construction – reconstructing antiquity’s largest infrastructure project. Construction Management and Economics, 36(6), 313–327. https://doi.org/10.1080/01446193.2017.1403639

Van Oyen, A. (2017). Agents and commodities: a response to Brughmans and Poblome (2016) on modelling the Roman economy. Antiquity, 91(359), 1356–1363. https://doi.org/10.15184/aqy.2017.138

Verhagen, P., Joyce, J., & Groenhuijzen, M. R. (2019). Finding the Limits of the Limes: modelling demography, economy and transport on the edge of the Roman Empire. Springer. https://doi.org/10.1007/978-3-030-04576-0_1

Verhagen, P., Joyce, J., & Groenhuizen, M. (2016). Modelling the Dynamics of Demography in the Dutch Roman Limes Zone. LAC 2014 Proceedings, 0(0), 13. https://doi.org/10.5463/lac.2014.62