Information acquisition strategies for Bayesian network-based decision support

Abstract

Determining how to utilize information acquisition resources optimally is a difficult task in the intelligence domain. Nevertheless, an intelligence analyst can expect little or no support for this from software tools today. In this paper, we describe a proof of concept implementation of a resource allocation mechanism for an intelligence analysis support system. The system uses a Bayesian network to structure intelligence requests, and the goal is to minimize the uncertainty of a variable of interest. A number of allocation strategies are discussed and evaluated through simulations.