Efficiently Executing Information-Gathering Plans

摘要

We describe Razor, a palnning-based informtion-gathering agent that assists users by automatically determining which Internet information sites are relevant to their query, accessing those sites in parallel, and integrating the results. Razor uses a disjunctive graph-based plan representation. It then uses a novel and powerufl form of local completeness reasoning in order to transform those plans into contingent plans of high quality. These contingent plans can be efficeintly executed, obtainign mroe answers at less cost than the original plans. We focus in this paper on the algorithms underlying the plan transformation process.