Articles by Luca Deravignone

For several years now archaeology has made use of methodologies based on Artificial Intelligence (AI) and Artificial Adaptive Systems (AAS). However, there are still only a few experiments that involve the spatial aspect, and in particular spatial analyses of the territory. Moreover, we are often faced with theoretical approaches, procedures that cannot be used or repeated by the scientific community because they are based on proprietary or undivulged algorithms. The first part of the paper is focused on a short historical retrospective of the applicative experiences of AI and GIS, from the New Archaeology pioneers to the latest experiments in predictive approaches. Subsequently, we present an open source application, both from the software as well as the procedural point of view, oriented to the creation of predictive maps and focused in particular on the study of ancient settlements.

Artificial neural networks are adaptive models that can be used for classification and pattern recognition purposes. ANNs do not differ from standard statistical models. The main difference between ANNs and traditional statistical models is their construction and definition process. In fact ANNs are adaptive in the sense that they can learn. Landscape Archaeology is a research area where the application of ANNs can be very useful. ANNs can be used for Landscape pattern recognition and Settlement systems modeling. This paper illustrate some aspects of the development of new tools and the application of ANNs in a raster GIS environment for archaeological predictive modeling purposes.