skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: The Use of Dynamic Stochastic Social Behavior Models to Produce Likelihood Functions for Risk Modeling of Proliferation and Terrorist Attacks

Abstract

The ability to estimate the likelihood of future events based on current and historical data is essential to the decision making process of many government agencies. Successful predictions related to terror events and characterizing the risks will support development of options for countering these events. The predictive tasks involve both technical and social component models. The social components have presented a particularly difficult challenge. This paper outlines some technical considerations of this modeling activity. Both data and predictions associated with the technical and social models will likely be known with differing certainties or accuracies – a critical challenge is linking across these model domains while respecting this fundamental difference in certainty level. This paper will describe the technical approach being taken to develop the social model and identification of the significant interfaces between the technical and social modeling in the context of analysis of diversion of nuclear material.

Authors:
; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
966018
Report Number(s):
PNNL-SA-59107
TRN: US0904014
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: International Conference on Probabilistic Safety Assessment and Management Conference: PSAM 9, May 18-23, 2008, Hong Kong, China
Country of Publication:
United States
Language:
English
Subject:
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION; DECISION MAKING; MANAGEMENT; PROBABILISTIC ESTIMATION; PROLIFERATION; RISK ASSESSMENT; SIMULATION; Predictive Modeling; Social Behavior Modeling; Dynamic Bayesian Networks; Risks of Terrorist Events; Nuclear Proliferation

Citation Formats

Young, Jonathan, Thompson, Sandra E, Brothers, Alan J, Whitney, Paul D, Coles, Garill A, Henderson, Cindy L, Wolf, Katherine E, and Hoopes, Bonnie L. The Use of Dynamic Stochastic Social Behavior Models to Produce Likelihood Functions for Risk Modeling of Proliferation and Terrorist Attacks. United States: N. p., 2008. Web.
Young, Jonathan, Thompson, Sandra E, Brothers, Alan J, Whitney, Paul D, Coles, Garill A, Henderson, Cindy L, Wolf, Katherine E, & Hoopes, Bonnie L. The Use of Dynamic Stochastic Social Behavior Models to Produce Likelihood Functions for Risk Modeling of Proliferation and Terrorist Attacks. United States.
Young, Jonathan, Thompson, Sandra E, Brothers, Alan J, Whitney, Paul D, Coles, Garill A, Henderson, Cindy L, Wolf, Katherine E, and Hoopes, Bonnie L. 2008. "The Use of Dynamic Stochastic Social Behavior Models to Produce Likelihood Functions for Risk Modeling of Proliferation and Terrorist Attacks". United States.
@article{osti_966018,
title = {The Use of Dynamic Stochastic Social Behavior Models to Produce Likelihood Functions for Risk Modeling of Proliferation and Terrorist Attacks},
author = {Young, Jonathan and Thompson, Sandra E and Brothers, Alan J and Whitney, Paul D and Coles, Garill A and Henderson, Cindy L and Wolf, Katherine E and Hoopes, Bonnie L},
abstractNote = {The ability to estimate the likelihood of future events based on current and historical data is essential to the decision making process of many government agencies. Successful predictions related to terror events and characterizing the risks will support development of options for countering these events. The predictive tasks involve both technical and social component models. The social components have presented a particularly difficult challenge. This paper outlines some technical considerations of this modeling activity. Both data and predictions associated with the technical and social models will likely be known with differing certainties or accuracies – a critical challenge is linking across these model domains while respecting this fundamental difference in certainty level. This paper will describe the technical approach being taken to develop the social model and identification of the significant interfaces between the technical and social modeling in the context of analysis of diversion of nuclear material.},
doi = {},
url = {https://www.osti.gov/biblio/966018}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Dec 01 00:00:00 EST 2008},
month = {Mon Dec 01 00:00:00 EST 2008}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: