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Addressing the Homeland Security Problem: A Collaborative Decision-Making Framework

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2665)

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.

Keywords

Inference Rule Connectionist Model Homeland Security Argument Structure National Monument 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  1. 1.W. P. Carey School of BusinessArizona State UniversityTempe
  2. 2.Department of Management Science & SystemsSchool of Management State University of New York at BuffaloBuffalo
  3. 3.Department of Management Science & Information SystemsUniversity of Texas at AustinAustin

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