This research has demonstrated that an MDL architecture such as the GRAVA system can be appropriated to generate possible solutions to interpretation problems, which span different semantic levels and incorporate different types of data. In doing so, a system has been constructed which has an emergent behaviour similar to that of human experts and generates possible, reasonable interpretations of texts to aid the experts in their task. Much can be done to improve the system described in this book, and to incorporate other types of information into the architecture to improve its functionality. There is scope for further research in almost every facet. Considerations of future work presented in this chapter focuses on two main areas: other possible approaches to knowledge elicitation to enable further understanding of how experts read ancient documents, and the enhancement and development of the MDL-based GRAVA system to increase its accuracy, and eventually deliver an application to the papyrologists. This chapter also highlights the overall contribution the research has made to its many constituent fields. An evaluation of the research is presented: the cognitive visual architecture developed being a testament to the value of interdisciplinary research.
Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.
If you think you should have access to this title, please contact your librarian.