Simulating Social Complexity to Understand the Archaeological Past
Large scale patterns, we commonly detect in the archaeological record, are often not a simple sum of individual human interactions but a complex interwoven network of dependencies among individuals, groups, and the environment in which they live. Unraveling this web is a hard task. Complexity science's answer to the challenges of understanding such non-linear, unpredictable, complex systems is computational modelling. Tools such as Agent-based Modelling, System Dynamics Models, Network Analysis or Equation-based Models are extensively used in virtually every scientific discipline and in the last decade have also gained ground in social sciences, anthropology and archaeology.In this session we present computational approaches to understanding the past, showcasing the innovative ways archaeologists have used simulation and model building to understand the complex societies they study. The session aim is to provide platform to discuss the potential and limitations of computational modelling in archaeology and highlight specific areas where it can be linked to more traditional empirical research.
Europe • North America - Southwest • Kingdom of Sweden (Country) • Kingdom of Norway (Country) • French Republic (Country) • United Kingdom of Great Britain and Nort (Country) • Ireland (Country) • Isle of Man (Country) • Kingdom of Belgium (Country) • Bailiwick of Guernsey (Country)
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Changing Channels: Simulating Irrigation Management on Evolving Canal Systems for the Prehistoric Hohokam of Central Arizona (2015)
Many Roman Bazaars: exploring the need for simple computational models in the study of the Roman economy (2015)
Simulating Late Holocene landscape use and the distribution of stone artefacts in arid western New South Wales, Australia (2015)