Problem localization strategies for pragmatics processing in natural-language front ends

Abstract

Problem localization is the identification of the most significant failures in the AND-OR tree resulting from an unsuccessful attempt to achieve a goal, for instance, in planning, backward-chaining inference, or top-down parsing. We examine heuristics and strategies for problem localization in the context of using a planner to check for pragmatic failures in natural language input to computer systems, such as a cooperative natural language interface to Unix∗∗. Our heuristics call for selecting the most hopeful branch at ORs, but the most problematic one at ANDs. Surprise scores and special-purpose rules are the main strategies suggested to determine this.