The Future of Knowledge Re resent at ion Extended Abstract

Knowledge representation (KR) has traditionally been thought of as the heart of artificial intelligence. Any-one who has ever built an expert system, a natural language system-almost any AI system at all-has had to tackle the problem of representing its knowl-edge of the world. Despite it ubiquity, for most of AI’s history KR has been a backstage activity. But in the 1980’s it emerged as a field unto itself, with its own burgeoning literature. Along with this growth, the last decade has seen major changes in KR methodol-ogy, important technical contributions, and challenges to the basic assumptions of the field. I survey some of these developments, and then speculate about some of the equally interesting changes that appear on the horizon. I also look at some of the critical problems facing KR research in the near future, both technical and sociological