Retrieval and Reasoning in Distributed Case Bases1

Abstract

The proliferation of electronically available networked information has led researchers to examine the issues involved in developing automated methods for gathering information in response to a query from a user. However, most of this literature deals with locating, gathering, and selecting the best response to a query from among a multitude of responses from different repositories or digital libraries. This paper deals with a different model of response to a query, involving composition of mutually related partial responses spread across a network of information repositories. We present a system for cooperative retrieval and composition of a case in which subcases are distributed across different agents in a multiagent system. From a Gestalt perspective, a good overall case may not be the one derived from the summation of best subcases. Each agent's local view may result in best local cases, which when assembled may not result in the best overall case in terms of global measures. We propose a negotiation-driven case retrieval algorithm as an approach to dynamically resolving inconsistencies between different case pieces during the retrieval process.