ABSTRACT
This chapter addresses the imbalance by briefly explaining the potential contribution of neural networks, artificial intelligence (AI) and virtual reality to overcome the limitations faced by the current technological status of GIS. Neural network architectures allied with classic ‘strong’ (AI) techniques offer the possibility of overcoming the most intractable and error-prone aspects of GIS data collection. GIS data input procedures are error prone and time consuming, and the data are often derived from a variety of different and incompatible sources. Time is of the essence to the archaeologist and, given the importance of the time dimension, it is perhaps surprising to find that archaeologists have hitherto paid scant attention to an understanding of the different concepts of time and the implications this may have for the understanding of prehistoric peoples. In archaeological terms, the ancient landscapes we seek to reconstruct are complex palimpsests of that interaction.
