A Fuzzy-Based Approach to Support Decision Making in Complex Military Environments

2016 ◽  
Vol 12 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Timothy P. Hanratty ◽  
E. Allison Newcomb ◽  
Robert J. Hammell II ◽  
John T. Richardson ◽  
Mark R. Mittrick
Keyword(s):  
Decision Making ◽  
Cyber Security ◽  
Human Performance ◽  
Performance Model ◽  
Military Intelligence ◽  
Conceptual Information ◽  
System Architectures ◽  
Cyber Intelligence ◽  
Soft Computing Techniques ◽  
The Military

Data for military intelligence operations are increasing at astronomical rates. As a result, significant cognitive and temporal resources are required to determine which information is relevant to a particular situation. Soft computing techniques, such as fuzzy logic, have recently been applied toward decision support systems to support military intelligence analysts in selecting relevant and reliable data within the military decision making process. This article examines the development of one such system and its evaluation using a constructive simulation and human performance model to provided critical understanding of how this conceptual information system might interact with personnel, organizational, and system architectures. In addition, similarities between military intelligence analysts and cyber intelligence analysts are detailed along with a plan for transitioning the current fuzzy-based system to the cyber security domain.

A Fuzzy-Based Approach to Support Decision Making in Complex Military Environments

Fuzzy Systems ◽  
2017 ◽  
pp. 1150-1182
Author(s):  
Timothy P. Hanratty ◽  
E. Allison Newcomb ◽  
Robert J. Hammell II ◽  
John T. Richardson ◽  
Mark R. Mittrick
Keyword(s):  
Decision Making ◽  
Cyber Security ◽  
Human Performance ◽  
Performance Model ◽  
Military Intelligence ◽  
Conceptual Information ◽  
System Architectures ◽  
Cyber Intelligence ◽  
Soft Computing Techniques ◽  
The Military

Data for military intelligence operations are increasing at astronomical rates. As a result, significant cognitive and temporal resources are required to determine which information is relevant to a particular situation. Soft computing techniques, such as fuzzy logic, have recently been applied toward decision support systems to support military intelligence analysts in selecting relevant and reliable data within the military decision making process. This article examines the development of one such system and its evaluation using a constructive simulation and human performance model to provided critical understanding of how this conceptual information system might interact with personnel, organizational, and system architectures. In addition, similarities between military intelligence analysts and cyber intelligence analysts are detailed along with a plan for transitioning the current fuzzy-based system to the cyber security domain.

Human Performance Modeling and Decision Analysis in a Concept Crew Workstation

2002 ◽  
Vol 46 (23) ◽  
pp. 1910-1914
Author(s):  
Thaddeus M. Wojcik
Keyword(s):  
Decision Making ◽  
Intelligent Agents ◽  
Human Performance ◽  
Control Unit ◽  
Performance Model ◽  
Task Demands ◽  
Ground Vehicles ◽  
Improved Performance ◽  
Operator Control ◽  
And Control

As part of the effort to evaluate the performance of soldiers operating in the Vetronics Testbed Technology (VTT), a human performance model of operator processes and tasks was developed. The purpose of this effort was to gather insight into operator workload constraints, points of operator overload due to task demands, and key decision-making points and strategies employed by the operators. Operator performance was modeled when the operators were confronted with the task of controlling multiple experimental unmanned ground vehicles (XUV) in addition to performing standard Command and Control (C2) operations. The model was built using the Improved Performance Research Integration Tool (IMPRINT). Development began with a task decomposition of the current VTT system and operator control unit (OCU) and was decomposed to the button-push level of operator interaction with the unit. Next, several operational scenarios were developed to drive the simulated operator actions in the OCU and obtain measures of performance. Finally, a decision-making architecture was implemented in the model to examine points where intelligent agents and system automation could potentially aid in reducing operator cognitive demands.

The Military Decision-Making Process: A Software Tutorial

1999 ◽  
Author(s):  
Elton Akins ◽  
Hank Dodge ◽  
Colleen Duffy ◽  
Brian Gollsneider ◽  
James Imlay
Keyword(s):  
Decision Making ◽  
Decision Making Process ◽  
The Military ◽  
Military Decision Making

Validating Human Performance Models: Building a House without Bricks

2020 ◽  
Vol 64 (1) ◽  
pp. 1511-1514
Author(s):  
Richard Steinberg ◽  
Raytheon Company ◽  
Alice Diggs ◽  
Raytheon Company ◽  
Jade Driggs
Keyword(s):  
Air Force ◽  
Human Performance ◽  
Control Program ◽  
Real Data ◽  
Performance Model ◽  
Force Model ◽  
Performance Models ◽  
Actual System ◽  
Support Design ◽  
Trade Offs

Verification and validation (V&V) for human performance models (HPMs) can be likened to building a house with no bricks, since it is difficult to obtain metrics to validate a model when the system is still in development. HPMs are effective for performing trade-offs between the human system designs factors including number of operators needed, the role of automated tasks versus operator tasks, and member task responsibilities required to operate a system. On a recent government contract, our team used a human performance model to provide additional analysis beyond traditional trade studies. Our team verified the contractually mandated staff size for using the system. This task demanded that the model have sufficient fidelity to provide information for high confidence staffing decisions. It required a method for verifying and validating the model and its results to ensure that it accurately reflected the real world. The situation caused a dilemma because there was no actual system to gather real data to use to validate the model. It is a challenge to validate human performance models, since they support design decisions prior to system. For example, crew models are typically inform the design, staffing needs, and the requirements for each operator’s user interface prior to development. This paper discusses a successful case study for how our team met the V&V challenges with the US Air Force model accreditation authority and successfully accredited our human performance model with enough fidelity for requirements testing on an Air Force Command and Control program.

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