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Exploring the Feasibility and Utility of Machine Learning-Assisted Command and Control

Exploring the Feasibility and Utility of Machine Learning-Assisted Command and Control - [Research Report]

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Publisher's Synopsis

This volume serves as the technical analysis to a report concerning the potential for artificial intelligence (AI) systems to assist in Air Force command and control (C2) from a technical perspective. The authors detail the taxonomy of ten C2 problem characteristics. They present the results of a structured interview protocol that enabled scoring of problem characteristics for C2 processes with subject-matter experts (SMEs). Using the problem taxonomy and the structured interview protocol, they analyzed ten games and ten C2 processes. To demonstrate the problem taxonomy and the structured interview protocol for a C2 problem, they then applied them to sensor management as performed by an air battle manager. The authors then turn to eight AI system solution capabilities. As for the C2 problem characteristics, they created a structured protocol to enable valid and reliable scoring of solution capabilities for a given AI system. Using the s

Book information

ISBN: 9781977407092
Publisher: RAND Corporation
Imprint: RAND Corporation
DEWEY: 355.80285
DEWEY edition: 23
Language: English
Weight: 137g
Height: 229mm
Width: 152mm
Spine width: 5mm