Building large knowledge-based systems: Representation and inference in the cyc project: D.B. Lenat and R.V. Guha

✍ Scribed by Drew McDermott

• Publisher: Elsevier Science
• Year: 1993
• Tongue: English
• Weight: 617 KB
• Volume: 61
• Category: Article
• ISSN: 0004-3702
• DOI: 10.1016/0004-3702(93)90093-q

✦ Synopsis

The Cyc project, and this book, are based on two premises: ( 1 ) that what is holding AI back is programs' lack of explicitly represented knowledge; and (2) that the time is ripe to fix the problem by encoding large chunks of it. The project aims to verify (2) by the most forthright means possible, namely, to carry out the encoding. This book is a report on the progress so far. It does not succeed in convincing me of either (1) or (2). However, it does get the juices flowing; if the time is not yet ripe for building a large knowledge base, the book makes you hope the time is coming soon.

Premise ( 1) is essentially taken for granted by Lenat and Guha. 1 There is a sort of Rip van Winkle quality at work here; they started building Cyc in 1984, and their consciousness got frozen at about that point. As it happens, there is a lot of skepticism about this premise in the AI community, and the authors don't address it. The skepticism stems from two sources: