MCC's CYC project is the building, over the coming decade, of a large knowledge base (or KB) of real world facts and heuristics and - as a part of the KB itself - methods for efficiently reasoning over the KB. As the title of this article suggests, our hypothesis is that of two major limitations to building large intelligent programs might be overcome by using such a system. We briefly illustrate how common sense reasoning and analogy can widen the knowledge acquisition bottleneck. The next section ('How CYC Works') illustrates how those same two abilities can solve problems of the type that stymie current expert systems. We then report how the project is being conducted currently: its strategic philosophy, its tactical methodology, and a case study of how we are currently putting that into practice. We conclude with a discussion of the project's feasibility and timetable.
CITATION STYLE
Lenat, D., Prakash, M., & Shepherd, M. (1986). CYC: USING COMMON SENSE KNOWLEDGE TO OVERCOME BRITTLENESS AND KNOWLEDGE ACQUISITION BOTTLENECKS. AI Magazine, 6(4), 65–85.
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