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DARPA Adaptive Capabilities Office – Adaptive Warfighting Architectures BAA – HR001122S0042

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DARPA Adaptive Capabilities Office – Adaptive Warfighting Architectures BAA – HR001122S0042

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The Adaptive Capabilities Office (ACO), working in close partnership with the military services, develops adaptive warfighting architectures that combine emerging technologies with new warfighting constructs to address the challenges faced by military forces. Over the past few decades, the effective projection of military power has become increasingly dependent on complex combinations of capabilities resident in all domains in order to achieve combined effects not possible from individual platforms or services. The combination of effects created by systems in or delivered through all domains, from the seafloor to space, including those via cyber and the electromagnetic spectrum, dictates a different approach to concept development. While in the past the delivery of effects could be described by linear ‘kill chains’ with a single execution path, this new level of complexity demands an understanding of ‘kill webs’- complex representations of effect chains with multiple possible paths that require adaptive architectures that can handle the rapidly changing context of modern combat. These adaptive architectures must be developed through a coherent campaign of study and analysis, constructive modeling and simulation (M&S), and live, virtual, and constructive experimentation. ACO is seeking innovative ideas and disruptive technologies that support this process and that focus on increasing the lethality and freedom of movement of U.S. military forces in complex battlefield conditions.
ACO is looking to advance the state-of-the-art across the entire detect-to-engage spectrum. Interests specifically include the following technical areas:
  • architecture
  • sensing and tracking
  • lethality
  • survivability
  • communications
  • advanced battle management
  • complex all-domain experimentation
  • relevant non-kinetic effects
  • faster than real time modeling and simulation
Abstracts accepted until 3 April 2023, full proposals until 2 June 2023 

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