AI systems must be able to manipulate their own internal representations automatically to deal with an infinitely complex and ever-changing world and to scale up to rich, complex applications. Such manipulation must go beyond changing beliefs and learning new concepts in terms of old concepts; it must be able to change an ontology's underlying syntax and semantics. Initial progress has been made, but further progress is urgently needed owing to the demands of autonomous multiagent systems. Understanding and automating this ability must be a major focus of AI for the next 50 years.This article is part of a special issue on the Future of AI.
Index Terms:
knowledge representation, ontology matching, fault diagnosis, multiagent systems, planning
Citation:
Alan Bundy, Fiona McNeill, "Representation as a Fluent: An AI Challenge for the Next Half Century," IEEE Intelligent Systems, vol. 21, no. 3, pp. 85-87, May/June 2006, doi:10.1109/MIS.2006.56