---
title: "Efficiently Executing Information-Gathering Plans"
authors:
  - "Marc T. Friedman"
  - "Daniel S. Weld"
doi: ""
url: "https://ijcai.org/proceedings/1997/114"
pdf: "https://ijcai.org/proceedings/1997/0114.pdf"
venue: "Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence"
year: 1997
pages: "785-790"
track: "Information Retrieval"
keywords:
---

# Efficiently Executing Information-Gathering Plans

Marc T. Friedman, Daniel S. Weld

*Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence*, pages 785-790.

## Abstract

We describe Razor, a planning-based information-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 graphbased plan representation. It then uses a novel and powerful form of local completeness reasoning in order to transform those plans into contingent plans of high quality. These contingent plans can be efficiently executed, obtaining more answers at less cost than the original plans. We focus in this paper on the algorithms underlying the plan transformation process.