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Journal ArticleDOI

Heuristic approaches to spatial analysis in archaeology

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TLDR
An approach to spatial analysis which is more closely tailored to archaeological objectives and archaeological data than are more "traditional" quantitative techniques such as nearest neighbor analysis is discussed.
Abstract
This article discusses an approach to spatial analysis which is more closely tailored to archaeological objectives and archaeological data than are more "traditional" quantitative techniques such as nearest neighbor analysis. Heuristic methods, methods which make use of the problem context and which are guided in part by intuitively derived "rules," are discussed in general and with reference to the problem of spatial analysis in archaeology. A preliminary implementation of such a method is described and applied to artificial settlement data and artifact distributions from the Magdalenian camp of Pincevent. Finally, the prospects for further development of heuristic methods are elaborated. SPATIAL ANALYSIS MAY BE SEEN as a process of searching for theoretically meaningful patterns in spatial data. Of course, this problem has been approached by archaeologists in several ways. The most obvious method of spatial analysis is the visual examination of a point distribution on a map with relevant background information in mind. This intuitive approach has been forsaken (and berated) by many archaeologists with greater aspirations to rigor, in favor of quantitative techniques of spatial analysis, such as nearest neighbor analysis. These techniques generally yield a summary statistic which attempts to characterize the spatial pattern with a single number and perhaps test its significance. The summary statistic is commonly compared from period to period or from area to area. This article reports the progress of an experiment in an alternative approach to the analysis of spatial patterns. This approach, the heuristic approach, is synthetic in that it attempts to open the way for the use of contextual knowledge and human expertise within a formal (computerexecuted) procedure for aiding human-directed spatial analysis. This presentation starts with a brief review of "traditional" quantitative approaches to spatial analysis. It is followed by a discussion of heuristic approaches to problem solving and their application to spatial analysis in archaeology. In the next section, heuristic procedures that have been developed are applied to artificial data sets and then to an analysis of actual data from the Magdalenian camp of Pincevent. The article closes with a discussion of the conclusions of this experiment and prospects for further development.

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Citations
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MonographDOI

Reading the past : current approaches to interpretation in archaeology

TL;DR: In this article, the problem of post-processual archaeology has been addressed and an ethnohistoric example: reconsideration of ethnoarchaeology and middle range theory.
Journal ArticleDOI

Measuring archaeological diversity by comparison with simulated assemblages

TL;DR: A method for measuring diversity is proposed that uses an archaeologically derived underlying frequency distribution of classes of artifacts to generate theoretical expectations for the number of different classes of items that should be found in a collection of a given total size.
Journal ArticleDOI

Intrasite Spatial Analysis of Bone: Subtracting the Effect of Secondary Carnivore Consumers

TL;DR: In this article, the position of a bone fragment on a limb bone, combined with bone surface modification, is used to identify a class of bone fragments that are minimally affected by carnivores and are thus the best indicators of spatial patterning resulting from human behavior.
Journal ArticleDOI

Describing and Comparing Archaeological Spatial Structures

TL;DR: An elaboration of the latter tactic is proposed here, that of characterizing spatial structure in terms of structural elements (or “grid cells”) and relationships among those elements, which enable the rigorous comparison of spatial structure among and between ethnoarchaeological and archaeological deposits.
References
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Book

Judgment Under Uncertainty: Heuristics and Biases

TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Book

The Sciences of the Artificial

TL;DR: A new edition of Simon's classic work on artificial intelligence as mentioned in this paper adds a chapter that sorts out the current themes and tools for analyzing complexity and complex systems, taking into account important advances in cognitive psychology and the science of design while confirming and extending Simon's basic thesis that a physical symbol system has the necessary and sufficient means for intelligent action.

Computer Science as Empirical Enquiry : Symbols and Search.

TL;DR: The Association for Computing Machinery as mentioned in this paper defined computer science as "the study of the phenomena surrounding computers." Computer science is the "study of the organism of the computer, not just the hardware, but the programmed, living machine".
Journal ArticleDOI

Computer science as empirical inquiry: symbols and search

TL;DR: The Association for Computing Machinery as discussed by the authors defined computer science as "the study of the phenomena surrounding computers." Computer science is the "study of the organism of the computer, not just the hardware, but the programmed, living machine".