Enhancing Battlefield Situational Awareness through Fuzzy-Based Value of Information

A major tenet of the US Army's data-to-decision initiative and a primary challenge for military commanders and their staff is the ability to shorten the cycle time from data gathering to decisions. Today, military operations require information from an unprecedented number of sources resulting in an unprecedented volume of collected data. Required are decision support technologies to improve the synthesis of data to decisions. Paramount to this process is the ability to better assess the applicability and relevance of information for decisions in complex military environments. Towards this end, this paper presents a soft computing approach and early results for calculating the Value of Information (VoI) in complex military environments using fuzzy associative memory as an effectively framework for contextually tuning its value based on content, reliability and latency.

[1]  Yawei Liang,et al.  An Approximate Reasoning Model for Situation and Threat Assessment , 2007, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007).

[2]  Robert J. Hammell,et al.  Capturing the value of information in complex military environments: A fuzzy-based approach , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[3]  Richard E. Hayes,et al.  Understanding Information Age Warfare , 2001 .

[4]  Robert J. Hammell,et al.  Computational Intelligence for Project Scope , 2011, MAICS.

[5]  G. Vincenti,et al.  Scouting for imprecise temporal associations to support effectiveness of drugs during clinical trials , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[6]  Parag Agrawal,et al.  Foundations of uncertain-data integration , 2010, Proc. VLDB Endow..

[7]  David E. Wilkins,et al.  Interactive Execution Monitoring of Agent Teams , 2003, J. Artif. Intell. Res..

[8]  Etienne Kerre.  On the concept of a linguistic variable , 1996 .

[9]  Markus Helfert,et al.  A Context Aware Information Quality Framework , 2009, 2009 Fourth International Conference on Cooperation and Promotion of Information Resources in Science and Technology.

[10]  Nancy J. Cooke,et al.  Knowledge Elicitation , 2003 .

[11]  Bin Yu,et al.  Managing the pedigree and quality of information in dynamic information sharing environments , 2007, AAMAS '07.

[12]  John Dumer,et al.  Knowledge Elicitation to Prototype the Value of Information , 2012, MAICS.

[13]  J. Yen,et al.  Fuzzy Logic: Intelligence, Control, and Information , 1998 .

[14]  Mica R. Endsley,et al.  Measurement of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[15]  Nancy J. Cooke,et al.  Varieties of knowledge elicitation techniques , 1994, Int. J. Hum. Comput. Stud..

[16]  Lotfi A. Zadeh,et al.  A Theory of Approximate Reasoning , 1979 .

[17]  Niv Ahituv,et al.  Assessing the value of information , 1989, ICIS '89.

[18]  Sheizaf Rafaeli,et al.  Experimental Investigation of the Subjective Value of Information in Trading , 2003, J. Assoc. Inf. Syst..

[19]  Sergei Vassilvitskii,et al.  Generalized distances between rankings , 2010, WWW '10.

[20]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[21]  Simon Parsons,et al.  Addendum to "Current Approaches to Handling Imperfect Information in Data and Knowledge Bases" , 1996, IEEE Trans. Knowl. Data Eng..

[22]  Michael T. Flynn,et al.  Fixing Intel: A Blueprint for Making Intelligence Relevant in Afghanistan , 2010 .

[23]  Matteo Magnani,et al.  A Survey on Uncertainty Management in Data Integration , 2010, JDIQ.

[24]  Sergio Guadarrama,et al.  Collecting fuzzy perceptions from non-expert users , 2010, International Conference on Fuzzy Systems.

[25]  Niv Ahituv,et al.  Assessing the value of information , 1989, ICIS '89.

[26]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[27]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[28]  Robert J. Hammell,et al.  Interpolation, Completion, and Learning Fuzzy Rules , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[29]  Robert J. Hammell,et al.  Employing Intelligent Decision Systems to Aid in Information Technology Project Status Decisions , 2010 .