Like us on Facebook!Follow us on Twitter!Follow us on LinkedIn!

By Thomas G. Whitley, Inna Moore, Gitisha Goel, and Damon Jackson

2010 In, "CAA 2009: Making History Interactive", Bernard Frischer, Jane Webb Crawford, and David Koller (editors), Archaeopress, Oxford, pp380-390

When we consider the intrinsic value of land units (or cells) in an archaeological analysis of landscape, settlement choice, or site selection, we tend to develop models which use static, unchanging costs or benefits, or which rely on least common denominators for a wide range of human actions or time frames. This is naturally driven by the tendency to find correlative evaluations as the most comforting means of both hypothesis building and hypothesis testing. Correlative approaches used in such applications as inductive predictive models are inherently reductionist and typically global-inferential. In actual application though, cell-based attractors are dynamic and distinctly contextual. Thus, we need to develop models that provide an egocentric, rather than a global, frame of reference, and are explanatory rather than merely correlative.

The first steps in this direction are provided by agent-based models; however, most agent-based models still utilize fixed frames of reference, or tools that rely on universal knowledge and global decision-making. Likewise, the acceptance of large dataset correlation testing, or training sets, as the primary means for assessing model success (even in agent-based models or neural network applications) precludes approaches that deal in sequential actions, local behaviors, or unique site types. Here we develop a model that uses cell-based analysis in several ways: First, attractor values are derivative of perception; the interface of knowledge and confidence in that knowledge. Second, spatial decision-making is temporally sequential; thus proximity tempers attractor values. And third, the scale of decision-making distinctly relies on both immediate and long-range planning and returns. These concepts will be illustrated with data from the Coastal Plain of Georgia (USA) and placed in the context of adaptations to a seemingly homogenous cultural and ecological landscape.

« Back