AI Bibliography
AI Bibliography |
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Niewood, E., Grant, G., & Lewis, T. (2019). A new battle command architecture for multi-domain operations: Countering peer adversary power projection MITRE CORP MCLEAN VA MCLEAN. |
| Resource type: Report/Documentation BibTeX citation key: Niewood2019 View all bibliographic details  |
Categories: Artificial Intelligence, Cognitive Science, Complexity Science, Computer Science, Data Sciences, Decision Theory, General, Military Science Subcategories: Augmented cognition, Big data, Command and control, Decision making, Doctrine, Edge AI, Human decisionmaking, JADC2, Mosaic warfare, Networked forces, Psychology of human-AI interaction, Strategy Creators: Grant, Lewis, Niewood Publisher: MITRE CORP MCLEAN VA MCLEAN Collection: |
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The 2018 National Defense Strategy shifts strategic focus to preparing for high-end conflict against peer adversaries – specifically Russia and China – where the Joint Force will face acute time, distance, and anti-access and area-denial (A2/AD) operational challenges. Halting Russian or Chinese aggression and degrading emplaced A2/AD networks will require the United States and its allies to rapidly plan and execute operations using capabilities from all domains, Services, and allies in a synchronized, cooperative, and efficient manner. Realizing simultaneous cross-domain operations will require a new approach to battle management and the supporting command and control (C2) architecture required to rapidly find, fix, and finish large sets of adversary mobile targets. Today, such synchronization at speed is difficult if not impossible. Military decision makers are dependent on legacy C2 systems impeded by multiple barriers, including those between domains, classification levels, the Services themselves, and our allies. |