Advances in Machine Learning Applications in Prehistoric Archaeology

The project “Advances in Machine Learning Applications in Prehistoric Archaeology: Spatio-Temporal Classification and Modelling of Archaeological and Archaeobotanical Data” explores the integration of artificial intelligence, machine learning, and computational simulation within archaeological research. It seeks to advance theoretical and methodological frameworks by developing innovative approaches to archaeological classification, chronological modelling, and the analysis of spatio-temporal dynamics.

A central objective of the project is to investigate the adoption of agriculture and animal husbandry during the Neolithic. To this end, a series of computational simulations of diverse prehistoric scenarios will be designed to reconstruct potential migratory processes and mechanisms of cultural transmission underlying the transformation of hunter-gatherer societies and the emergence of new social and economic systems.