Addressing the homeland security problem: A collaborative decision-making framework

Raghu Santanam, R. Ramesh, Andrew B. Whinston

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

A key underlying problem intelligence agencies face in effectively combating threats to homeland security is the diversity and volume of information that need to be disseminated, analyzed and acted upon. This problem is further exacerbated due to the multitude of agencies involved in the decision-making process. Thus the decision-making processes faced by the intelligence agencies are characterized by group deliberations that are highly ill structured and yield limited analytical tractability. In this context, a collaborative approach to providing cognitive support to decision makers using a connectionist modeling approach is proposed. The connectionist modeling of such decision scenarios offers several unique and significant advantages in developing systems to support collaborative discussions. Several inference rules for augmenting the argument network and to capture implicit notions in arguments are proposed. We further explore the effects of incorporating notions of information source reliability within arguments and the effects thereof.

Original languageEnglish (US)
Pages (from-to)249-265
Number of pages17
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2665
StatePublished - Dec 1 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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