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Authors: Gregory M. Chavez ; Brian P. Key ; David K. Zerkle and Daniel W. Shevitz

Affiliation: Los Alamos National Laboratory, United States

Keyword(s): Imprecise Information, Confidence, Triage application.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Computational Intelligence ; Expert Systems ; Fuzzy Systems ; Health Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge Representation and Reasoning ; Knowledge-Based Systems ; Model-Based Reasoning ; Natural Language Processing ; Pattern Recognition ; Soft Computing ; Symbolic Systems ; Uncertainty in AI

Abstract: The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. Extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.

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Paper citation in several formats:
M. Chavez, G.; P. Key, B.; K. Zerkle, D. and W. Shevitz, D. (2010). INFORMATION UNCERTAINTY TO COMPARE QUALITATIVE REASONING SECURITY RISK ASSESSMENT RESULTS. In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-674-021-4; ISSN 2184-433X, SciTePress, pages 398-405. DOI: 10.5220/0002748103980405

@conference{icaart10,
author={Gregory {M. Chavez}. and Brian {P. Key}. and David {K. Zerkle}. and Daniel {W. Shevitz}.},
title={INFORMATION UNCERTAINTY TO COMPARE QUALITATIVE REASONING SECURITY RISK ASSESSMENT RESULTS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2010},
pages={398-405},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002748103980405},
isbn={978-989-674-021-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - INFORMATION UNCERTAINTY TO COMPARE QUALITATIVE REASONING SECURITY RISK ASSESSMENT RESULTS
SN - 978-989-674-021-4
IS - 2184-433X
AU - M. Chavez, G.
AU - P. Key, B.
AU - K. Zerkle, D.
AU - W. Shevitz, D.
PY - 2010
SP - 398
EP - 405
DO - 10.5220/0002748103980405
PB - SciTePress

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