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Department of Archaeology

 
Read more at: ArchBiMod – Agent-Based Modelling to assess the quality and bias of the archaeological record

ArchBiMod – Agent-Based Modelling to assess the quality and bias of the archaeological record

Archaeological data is often biased and incomplete. This is a well-known issue for most archaeologists. Although studies of specific sites and small regions can have this into account, the effect of this problem increases exponentially as archaeologists expand their chronological and geographic frame, and try to answer questions related to general dynamics and broad human processes.


Read more at: EHSCAN-Exploring Early Holocene Saharan Cultural Adaptation and Social Networks through socio-ecological inferential modelling

EHSCAN-Exploring Early Holocene Saharan Cultural Adaptation and Social Networks through socio-ecological inferential modelling

EHSCAN is a Horizon-MSCA-2022-PF scheme Fellowship Funded by UKRI and hosted by the McDonald Institute for Archaeological Research, University of Cambridge. 


Read more at: Transitions in early stone tool technologies: a computer vision and machine learning approach

Transitions in early stone tool technologies: a computer vision and machine learning approach

The transition from Oldowan to Acheulean technologies are hypothesised to be concomitant with advances in cognition and behaviour. However, the nature of these shifts, and their cultural and evolutionary implications are poorly defined and understood. While extensive literature exists on these technologies, significant differences in research methods and traditions make comparative and comprehensive analyses problematic.