FUNCTIONAL ANALYSIS FROM VISUAL AND NON-VISUAL DATA . AN ARTIFICIAL INTELLIGENCE APPROACH

Why archaeological artefacts are the way they are? In this paper we try to solve such a question by investigating the relationship between form and function. We propose new ways of studying the way behaviour in the past can be asserted on the examination of archaeological observables in the present. In any case, we take into account that there are also non-visual features characterizing ancient objects and materials (i.e., compositional information based on mass spectrometry data, chronological information based on radioactive decay measurements, etc.). Information that should make us aware of many functional properties of objects is multidimensional in nature: size, which makes reference to height, length, depth, weight and mass; shape and form, which make reference to the geometry of contours and volumes; texture, which refers to the microtopography (roughness, waviness, and lay) and visual appearance (colour variations, brightness, reflectivity and transparency) of surfaces; and finally material, meaning the combining of distinct compositional elements and properties to form a whole. With the exception of material data, the other relevant aspects for functional reasoning have been traditionally described in rather ambiguous terms, without taking into account the advantages of quantitative measurements of shape/form, and texture. Reasoning about the functionality of archaeological objects recovered at the archaeological site requires a cross-disciplinary investigation, which may also range from recognition techniques used in computer vision and robotics to reasoning, representation, and learning methods in artificial intelligence. The approach we adopt here is to follow current computational theories of object perception to ameliorate the way archaeology can deal with the explanation of human behaviour in the past (function) from the analysis of visual and non-visual data, taking into account that visual appearances and even compositional characteristics only constrain the way an object may be used, but never fully determine it. FUNCTIONAL ANALYSIS FROM VISUAL AND NON-VISUAL DATA. AN ARTIFICIAL INTELLIGENCE APPROACH J.A. Barceló, V. Moitinho de Almeida Universitat Autònoma de Barcelona, Dept. of Prehistory, Quantitative Archaeology Lab, Edifici B Facultat de Filosofia i Lletres 08193 Bellaterra (Barcelona), Spain Corresponding author: juanantonio.barcelo@uab.es Received: 3/8/2012 Accepted: 21/11/2012