AN AGENT-BASED MODEL OF HUMAN DISPERSALS AT A GLOBAL SCALE

Simone Callegari (), John David Weissmann (), Natalie Tkachenko (), Wesley P. Petersen (), George Lake (), Marcia Ponce de León () and Christoph P. E. Zollikofer ()
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Simone Callegari: Anthropological Institute and Museum, University of Zurich, Winterthurerstr. 190, 8057 Zürich, Switzerland
John David Weissmann: Anthropological Institute and Museum, University of Zurich, Winterthurerstr. 190, 8057 Zürich, Switzerland
Natalie Tkachenko: Institute for Theoretical Physics, University of Zurich, Winterthurerstr. 190, 8057 Zürich, Switzerland
Wesley P. Petersen: Anthropological Institute and Museum, University of Zurich, Winterthurerstr. 190, 8057 Zürich, Switzerland
George Lake: Institute for Theoretical Physics, University of Zurich, Winterthurerstr. 190, 8057 Zürich, Switzerland
Marcia Ponce de León: Anthropological Institute and Museum, University of Zurich, Winterthurerstr. 190, 8057 Zürich, Switzerland
Christoph P. E. Zollikofer: Anthropological Institute and Museum, University of Zurich, Winterthurerstr. 190, 8057 Zürich, Switzerland

Advances in Complex Systems (ACS), 2013, vol. 16, issue 04n05, 1-21

Abstract: In this paper, we report on the theoretical foundations, empirical context and technical implementation of an agent-based modeling (ABM) framework, that uses a high-performance computing (HPC) approach to investigate human population dynamics on a global scale, and on evolutionary time scales. The ABM-HPC framework provides anin silicotestbed to explore how short-term/small-scale patterns of individual human behavior and long-term/large-scale patterns of environmental change act together to influence human dispersal, survival and extinction scenarios. These topics are currently at the center of the Neanderthal debate, i.e., the question why Neanderthals died out during the Late Pleistocene, while modern humans dispersed over the entire globe. To tackle this and similar questions, simulations typically adopt one of two opposing approaches, top-down (equation-based) and bottom-up (agent-based) models of population dynamics. We propose HPC technology as an essential computational tool to bridge the gap between these approaches. Using the numerical simulation of worldwide human dispersals as an example, we show that integrating different levels of model hierarchy into an ABM-HPC simulation framework provides new insights into emergent properties of the model, and into the potential and limitations of agent-based versus continuum models.

Keywords: Agent-based models; dispersals; ecology; high-performance computing; palaeoanthropology; spatiotemporal population dynamics (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:16:y:2013:i:04n05:n:s0219525913500239

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DOI: 10.1142/S0219525913500239

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