An Agent-Based Model of Human Dispersals at a Global Scale

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 an in silico testbed 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.

Dispersal and the Movius Line: Testing the effect of dispersal on population density through simulation

“…Computational modelling (simulation) is an increasingly important approach in archaeology to the challenges of researching complex systems, that is systems in which numerous individual parts interact with each other in a non-linear way, producing aggregated behaviour that cannot be easily predicted solely on the basis of their individual characteristics (Mitchell, 2009, pp.12-4;Barton, 2014). A number of simulation techniques have been used before to investigate various aspects of human mobility patterns and different ancient dispersals (overview in: Romanowska 2015a), including equation-based modelling (e.g., Steele et al 1998;Steele 2009;Fort 2012), cellular automata (e.g., Mithen and Reed 2002;Nikitas and Nikita 2005) and agent-based modelling (e.g., Wren et al 2014;Scherjon 2013) or a combination of the above (e.g., Young 2002;Callegari et al 2013). Similarly, this model shares a number of features with all of the three most commonly used approachescellular automata, equation-based modelling and individual-based modelling.…”

A Stable Finite-Difference Scheme for Population Growth and Diffusion on a Map

“…For this choice of T s , we still have to choose r , D . Some estimates were known [4, 5] to be approximately D ≈ 200km 2 /yr and r ≈ 2.0 × 10 −3 yr −1 . With the hope that we might be more precise, we optimize on the following RMS parameter, where arch MC = earliest estimated population of Meadowcroft, PA; similarly, arch FC = earliest known population of Fell’s Cave, near the tip of Cape Horn, Isla Grande, Tierra del Fuego [29, 30].…”

“…There is considerable interest in modeling population dynamics at large spatial and temporal scales, for example the modern human out-of-Africa dispersal [1–4] or Neanderthal dispersal and extinction [5]. These models are required to interpret local and global patterns of genetic, phenetic and cultural variation [1, 6–9].…”

So You Think You Can Model? A Guide to Building and Evaluating Archaeological Simulation Models of Dispersals

“…A classic example is the study of the Neolithic spread into Europe through equation-based models (Wirtz and Lemmen 2003;Hazelwood and Steele 2004;Ackland et al 2007;Lemmen et al 2011;Baggaley et al 2012;Fort 2012;Fort et al 2012;Isern and Fort 2012). Other common research topics include the Palaeolithic dispersals (Mithen and Reed 2002;Scherjon 2013;Callegari et al Pre-print version. Visit digitalcommons.wayne.edu/humbiol after publication for the final version.…”

“…It allows researchers to describe their models using the same categories, thus facilitating the comparison between models and guiding readers through not only the technical details of the simulation but also the intentions of the authors. The ODD format has been commonly used to describe archaeological ABMs (e.g., Callegari et al 2013;Scherjon 2013;Davies and Bickler 2015). Finally, to ensure reproducibility, modellers are urged to give full access to the source code of their simulations (Ince et al 2012;Collberg et al 2014) and are encouraged to have the code peer- …”