Toward The Development Of A Predictive Computer Model Of Decision Making During Uncertainty For Use In Simulations Of U S Army Command And Control System
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Toward the Development of a Predictive Computer Model of Decision Making During Uncertainty for Use in Simulations of U.S. Army Command and Control System
In today's increasingly complex world of digital command and control, it is seldom obvious or intuitive how the introduction of new automation systems will affect the overall performance of battlefield command and control (C2) systems. Field observations can account for performance factors that are directly observable, such as rates of communication flow, rates of flow, and quality of incoming intelligence. However, what the human mind does under the influence of all these factors is not directly observable and is the subject of considerable experimentation. This research addresses this limitation through the development of predictive quantitative models of decision making during conditions of uncertainty such as exist in many aspects of human performance and certainly in battlespace management. Using Bayesian statistical approaches implemented through Partially Observable Markov Decision Processes (POMDP) that describe experiential decision processes moderated by Monte Carlo effects to account for performance variability, we are developing a series of computer simulations with the goal of predicting the quality of decisions possible from a given set of input conditions. These simulations are based on cognitive models being developed in a collaborative effort through a series of empirical studies that investigate human performance in a sequential decision making with uncertainty task using human subjects. Through this collaboration, the results of these studies are being applied at each stage of the research to predictive computer simulations of Army battlefield performance where battlefield automated C2 systems are involved. These simulations, when operational, will allow cognitive effects, such as predictive levels of effective decisions possible from a given set of circumstances, to be assessed as a battlefield metric.
Toward the Development of a Predictive Computer Model of Decision Making During Uncertainty for Use in Simulations of U.S. Army Command and Control Systems
In today's increasingly complex world of digital command and control, it is seldom obvious or intuitive how the introduction of new automation systems will affect the overall performance of battlefield command and control (C2) systems. Field observations can account for performance factors that are directly observable, such as rates of communication flow, rates of flow, and quality of incoming intelligence. However, what the human mind does under the influence of all these factors is not directly observable and is the subject of considerable experimentation. This research addresses this limitation through the development of predictive quantitative models of decision making during conditions of uncertainty such as exist in many aspects of human performance and certainly in battlespace management. Using Bayesian statistical approaches implemented through Partially Observable Markov Decision Processes (POMDP) that describe experiential decision processes moderated by Monte Carlo effects to account for performance variability, we are developing a series of computer simulations with the goal of predicting the quality of decisions possible from a given set of input conditions. These simulations are based on cognitive models being developed in a collaborative effort through a series of empirical studies that investigate human performance in a sequential decision making with uncertainty task using human subjects. Through this collaboration, the results of these studies are being applied at each stage of the research to predictive computer simulations of Army battlefield performance where battlefield automated C2 systems are involved. These simulations, when operational, will allow cognitive effects, such as predictive levels of effective decisions possible from a given set of circumstances, to be assessed as a battlefield metric.
Research Anthology on Military and Defense Applications, Utilization, Education, and Ethics
Author: Management Association, Information Resources
language: en
Publisher: IGI Global
Release Date: 2021-05-28
Military technology is highly advanced in terms of technology being used in the field, computer applications, artificial intelligence, and software applications. These high-performance technologies range from weapons to communications technology to automation in vehicles and weaponry. These technologies must be both secure and reliable in harsh environments. Research is being focused specifically on that, including how military and defense applications operate, what modern technologies are being used, and the ethics surrounding these applications. A holistic view of these applications is necessary for both understanding current military tactics and tools along with the future applications. The Research Anthology on Military and Defense Applications, Utilization, Education, and Ethics focuses specifically on military and defense operations, expenditure, technologies, and tools, and the ethics surrounding technologies like weaponry and artificial intelligence in the military. The chapters cover a wide and diverse range of military and defense applications while providing crucial information on the functions, security, and reliability of these technologies. Beyond an understanding of the applications themselves, this book also focuses on military education surrounding these technologies and the ethics of usage to provide a well-rounded understanding of research in the field. This book is ideal for military consultants, military personnel, defense agencies, national security agencies, government officials, defense personnel, policymakers, military educators and trainers, stakeholders, practitioners, researchers, academicians, and students interested in the latest research in military and defense applications.