Application of an entropy maximizing and dynamics model for understanding settlement structure: the Khabur Triangle in the Middle Bronze and Iron Ages

Davies, T.; Fry, Hannah; Wilson, Alan; Palmisano, Alessio; Altaweel, Mark; Radner, Karen

doi:10.1016/j.jas.2013.12.014

Cited by 33 publications

(48 citation statements)

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“…The range of applications of such modeling now appearing suggests that this approach is mature enough that we should look to include uncertainty as an intrinsic part of such work. Our view echoes that of other authors who tackle other aspects of the uncertainty problem (e.g., Bevan and Wilson, 2013;Davies et al, 2014;Paliou and Bevan, 2016). Using these emerging approaches to account for uncertainty will only enhance the contribution modeling can make to our overall picture of the past.…”

Section: Resultssupporting

confidence: 71%

“…This context was chosen so that we can illustrate general methodological principles with a practical archeological example, with the added benefit that it allows us to make direct contact with the classic work of Wilson (1987, 1991). The last decade has seen a rise in the use of such modeling techniques on settlement patterns in a wide range of times and other places: Crete in the second millennium BC (Bevan and Wilson, 2013) or the Middle Bronze Age (Evans et al, 2006;Knappett et al, 2008Knappett et al, , 2011Paliou and Bevan, 2016), Iron Age NE Syria (Davies et al, 2014), early second millennium BC Central Anatolia (Palmisano and Altaweel, 2015), late first Millennium Latenian urbanization (Filet, 2017), early Japan (Mizoguchi, 2009), the Maya lowlands (Ducke and Kroefges, 2008), to give just a few examples. Similar methods can be used when modeling of other types of spatial organization, such as lithic assemblages (Wilson, 2007) to name just one.…”

Section: Resultsmentioning

confidence: 99%

“…Another approach to the uncertainty around our selection of sites could be to try different random subsets of known sites. Again repeating measurements several times will allow us to judge how site location uncertainty effects our conclusions, for example, see the study by Davies et al (2014).…”

Section: Sitesmentioning

confidence: 99%

“…Specifically, the question is to understand to what extent spatial features can explain why certain settlements out of the many in the region came to dominate it. The success of the model led to its adoption for understanding city-state formation in other times and other places: second millennium BC Crete (Bevan and Wilson, 2013), Middle Bronze Age and Iron Age NE Syria (Davies et al, 2014), early second millennium BC Central Anatolia (Palmisano and Altaweel, 2015), and late first millennium Latenian urbanization (Filet, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Was Thebes Necessary? Contingency in Spatial Modeling

Evans

Rivers

2017

Front. Digit. Humanit.

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When data are poor, we resort to theory modeling. This is a two-step process. We have first to identify the appropriate type of model for the system under consideration and then to tailor it to the specifics of the case. To understand settlement formation, which is the concern of this article, this involves choosing not only input parameter values such as site separations but also input functions that characterizes the ease of travel between sites. Although the generic behavior of the model is understood, the details are not. Different choices will necessarily lead to different outputs (for identical inputs). We can only proceed if choices that are "close" give outcomes that are similar. Where there are local differences, it suggests that there was no compelling reason for one outcome rather than the other. If these differences are important for the historic record, we may interpret this as sensitivity to contingency. We re-examine the rise of Greek city-states as first formulated by Rihll and Wilson in 1979, initially using the same "retail" gravity model. We suggest that, although cities like Athens owe their position to a combination of geography and proximity to other sites, the rise of Thebes is the most contingent, whose success reflects social forces outside the grasp of simple network modeling.

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Section: Resultssupporting

confidence: 71%

Section: Resultsmentioning

confidence: 99%

Section: Sitesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Was Thebes Necessary? Contingency in Spatial Modeling

Evans

Rivers

2017

Front. Digit. Humanit.

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“…The model has its origins in the shopping model initially developed by Huff (1963) and Lakshmanan and Hansen (1965) and shares many similarities to the gravity models widely used in location theory and urban planning (Isard, 1975;Senior, 1979). It was later formalised by Wilson and Wilson (1971), embedded into a dynamic Lotka-Volterra type system (Harris and Wilson, 1978) and has since been adapted to a range of applications in theory and practice, including trade (Fry, 2012), migration (Dennett and Wilson, 2013), higher education (Singleton et al, 2012), policing strategy (Baudains et al, 2013;Davies et al, 2013), analysis of archaeological sites (Davies et al, 2014) and distribution of city sizes (Favaro and Pumain, 2011).…”

Section: Introductionmentioning

confidence: 99%

Rate effects on the growth of centres

Fry

Smith

2016

Eur. J. Appl. Math

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Entropy maximising spatial interaction models have been widely exploited in a range of disciplines and applications: from trade and migration flows to the spread of riots and the understanding of spatial patterns in archaeological sites of interest. When embedded into a dynamic system and framed in the context of a retail model, the dynamics of centre growth poses an interesting mathematical problem, with bifurcations and phase changes, which may be addressed analytically. In this paper, we present some analysis of the continuous retail model and the corresponding discrete version, which yields insights into the effect of space on the evolving system, and an understanding of why certain retail centres are more successful than others. The slowly developing growths and the fast explosive growths that are of particular concern are explained in detail.

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Modelling of Pathways and Movement Networks in Archaeology: An Overview of Current Approaches

Verhagen

Nuninger

Groenhuijzen

2019

Computational Social Sciences

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This chapter presents and discusses current approaches and trends in computer-based modelling of pathways and movement networks in archaeology. After an introduction to the theoretical concepts involved, we present a state of the art of methodologies applied for reconstructing pathways and movement in ancient landscapes and discuss the various difficulties in using these methods as well as the most important technical hurdles involved. The problems of integrating optimal pathfinding algorithms with 'softer' socio-cultural variables are highlighted, as well as the limitations of modelling connections between places using least-cost path techniques. Network analysis reconstruction and analysis approaches are then reviewed as tools to better understand the overall structure of movement and communication in ancient landscapes. It is concluded that, while the potential of current approaches for understanding ancient movement is considerable, improvement is still needed in three main areas: the integration of approaches, sensitivity analysis and validation, and the theoretical underpinning of models of ancient movement.

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Application of an entropy maximizing and dynamics model for understanding settlement structure: the Khabur Triangle in the Middle Bronze and Iron Ages

Cited by 33 publications

References 10 publications

Was Thebes Necessary? Contingency in Spatial Modeling

Was Thebes Necessary? Contingency in Spatial Modeling

Rate effects on the growth of centres

Modelling of Pathways and Movement Networks in Archaeology: An Overview of Current Approaches

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