Using Fuzzy Cognitive Maps for Knowledge Management in a Conflict Environment

In modern military battlefield environments, the availability of data and information has increased exponentially. Through information and communications technology, individuals and teams can access real-time data about almost any aspect of their current conflict situation, but this instantaneous availability of information to individuals and teams in these conflict situations does not always result in better or faster decisions. Instead, the speed and volume of data made available through surveillance, monitoring, analysis, computer, and communications technology can quickly overwhelm decision makers. Worse, different decision makers that need to coordinate their actions as part of a team effort might use different filters to reduce their data to something more manageable, or what they perceive as more relevant, to their emerging situation. To better manage the information in real time, a mediator is necessary. Fuzzy cognitive maps are proposed as one possible technique for mediating the information made available to decision makers. Such maps were used as part of a research project that used novice teams to simulate an Airborne Warning and Control System (AWACS) crew managing air assets in a conflict situation. The process of constructing the maps, their role in the simulation, and preliminary results of the test runs of the AWACS simulation are presented

[1]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[2]  N. Moray,et al.  Adaptive automation, trust, and self-confidence in fault management of time-critical tasks. , 2000 .

[3]  Michael D. McNeese,et al.  Modeling, measuring, and mediating teamwork: the use of fuzzy cognitive maps and team member schema similarity to enhance BMC/sup 3/I decision making , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[4]  Philip H. Marsden,et al.  Allocation of functions , 2004 .

[5]  G. Salomon.  Distributed cognitions : psychological and educational considerations , 1997 .

[6]  Joseph G. Wohl,et al.  Force Management Decision Requirements for Air Force Tactical Command and Control , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Michael D. McNeese.  Socio-Cognitive Factors in the Acquisition and Transfer of Knowledge , 2000, Cognition, Technology & Work.

[8]  E. Hutchins.  Cognition in the wild , 1995 .

[9]  Michael D. McNeese,et al.  A Situated Cognition Approach to Problem Solving with Implications for Computer-Based Learning and Assessment , 1993, HCI.

[10]  Nadine B. Sarter,et al.  How in the World Did We Ever Get into That Mode? Mode Error and Awareness in Supervisory Control , 1995, Hum. Factors.

[11]  William B. Rouse,et al.  The role of mental models in team performance in complex systems , 1992, IEEE Trans. Syst. Man Cybern..

[12]  Michael D. McNeese,et al.  Qualitative modeling of complex systems for cognitive engineering , 1999, Defense, Security, and Sensing.

[13]  Stephen M. Hess,et al.  Development of a Team-in-the-Loop, Synthetic Simulation Environment Based on Data from Cognitive Task Analysis , 1999 .

[14]  B. Rouse William,et al.  Adaptive Aiding for Human/Computer Control , 1988 .

[15]  Michael D. McNeese,et al.  Understanding and Modeling Information Dominance in Battle Management: Applications of Fuzzy Cognitive Maps , 1998 .

[16]  R. Hall,et al.  Members of great teams think alike: A model of team effectiveness and schema similarity among team members. , 1994 .

[17]  Eduardo Salas,et al.  Making decisions under stress: Implications for individual and team training. , 1998 .

[18]  Emilie M. Roth,et al.  Predicting Vulnerabilities in Computer-Supported Inferential Analysis under Data Overload , 2001, Cognition, Technology & Work.

[19]  Endsley,et al.  A model of inter- and intrateam situation awareness: implications for design, training and measurement , 2001 .

[20]  Andrew P. Sage,et al.  Behavioral and Organizational Considerations in the Design of Information Systems and Processes for Planning and Decision Support , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[21]  Michael D. McNeese,et al.  Computer-supported collaborative work: a new agenda for human factors engineering , 1992, Proceedings of the IEEE 1992 National Aerospace and Electronics Conference@m_NAECON 1992.

[22]  Kjeld Schmidt,et al.  Taking CSCW Seriously: Supporting Articulation Work * , 1992 .

[23]  Michael D. McNeese,et al.  Distributed Cognition in Shared Information Spaces , 2002 .

[24]  Kjeld Schmidt,et al.  Taking CSCW seriously , 1992, Computer Supported Cooperative Work (CSCW).

[25]  Michael D. McNeese,et al.  Using Fuzzy Cognitive Maps to Define the Search Space in Problem Solving , 1997, HCI.

[26]  Michael D. McNeese,et al.  The Social Psychology of Intelligent Machines: A Research Agenda Revisited , 1999, HCI.

[27]  Michael D. McNeese,et al.  Computer Aided Cognition to Support Problem-Centered Decomposition of Complex Problems , 2003 .

[28]  Gary Klein,et al.  Naturalistic Decision Making , 2008, Hum. Factors.

[29]  James G. Greeno,et al.  Situativity and Symbols: Response to Vera and Simon , 1993, Cogn. Sci..

[30]  Donald A. Norman,et al.  Things that make us smart , 1979 .

[31]  N. Moray,et al.  Adaptive automation, trust, and self-confidence in fault management of time-critical tasks. , 2000, Journal of experimental psychology. Applied.