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27.03.2018

Modelling Prehistoric Hunting Behaviour (MPJ)

The aim of the project is to improve and extend the empirical basis of theoretical and computational models of prehistoric hunting behavior. To this end, indigenous experts in Namibia will be accompanied on their traditional hunting trips, i.e. on foot and without firearms, visual aids or hunting dogs. The associated data (GPS movement paths, calorie consumption, video and audio recordings of decision-making processes, etc.) will be collected to gain insights into human behavior during hunting, physical constraints on human mobility, and interactions between humans, animals and the environment. To date, such data have not been collected directly, but theorized or derived from other contexts. This information will then be integrated into existing theoretical and computational models of hunter-gatherer societies, in particular agent-based models (ABM) to simulate dynamic aspects of human behavior in the landscape. It is expected that the collected data and the proposed computational models will contribute to a better understanding of hunter-gatherer practices in arid landscapes and will further advance theoretical model-building efforts in archaeology. Furthermore, they will promote the development of computational approaches that are better tailored to the needs of archaeology and, more broadly, hunter-gatherer research in general.

The project is closely linked to the research project "Indigenous Knowledge and Archaeoinformatics (IKAi)" funded by the Volkswagen Foundation.

PIs: Prof. Dr. Eleftheria Paliou (Archaeoinformatics), Dr. Tilman Lenssen-Erz (UFG, Africa Research Center)

Research staff and partners: https://ikai.phil-fak.uni-koeln.de/das-team

Further information: https://www.geistes-und-sozialwissenschaften-bmbf.de/de/Digital-Humanities-Wie-jagten-unsere-Vorfahren-2341.html

Funding: BMBF, funding program “Support for research and development projects for the theoretical, methodological and technical development of the digital humanities”

 

 

 

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