FAWCETT@RED.RUTGERS.EDU (Tom Fawcett) (10/30/86)
TITLE: Memory Access Techniques for a Case-based Learning System SPEAKER: Wendy Lehnert DATE: Monday, November 3 LOCATION: Princeton University, Green Hall, Langfeld Lounge TIME: 12:00 - 1:00 p.m. Abstract Traditionally, symbolic processing techniques in artificial intelligence have addressed "high-level" cognitive tasks like expert reasoning, natural language processing, and knowledge acquisition. At the same time, a separate paradigm of connectionist techniques has addressed "low-level" perceptual problems like word recognition, stereoscopic vision and speech recognition. While symbolic computation models are frequently characterized as brittle, difficult to extend, and exceedingly fragile, many connectionist models exhibit graceful degradation and natural methodologies for system expansion. In this talk, we will look at how connectionist techniques might be useful as a strategy for indexing symbolic memory. Our discussion will focus on two seemingly unrelated tasks: word pronunciation and narrative summarization. We will endeavor to show how both problems can be approached with similar strategies for indexing memory and resolving competing indices. -------