Agent based predictive models in archaeology
Rocks-Macqueen, James Douglas
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For over 40 years archaeologists have been using predictive modelling to locate archaeological sites. While great strides have been made in the theory and methods of site predictive modelling there are still unresolved issues like a lack of theory, poor data, biased datasets and poor accuracy and precision in the models. This thesis attempts to address the problems of poor model performance and lack of theory driven models through the development of a new method for predictive modelling, agent based modelling. Applying GIS and agent based modelling tools to a project area in southeaster New Mexico this new methodology explored possible behaviours that resulted in site formation such as access to water resources, travel routes and resource exploitation. The results in regards to improved accuracy over traditional methods were inconclusive as a data error was found in the previously created predictive models for the area that were to be used as a comparison. But, the project was more successful in providing explanatory reasons for site placement based on the models created. This work has the potential to open up predictive modelling to wider archaeology audiences, such as those based at universities. Additional findings also impacted other areas of archaeological investigation outside of predictive modelling, such as least cost path analyses and resource gathering analyses.