Abstract: The goal of the proposed research is to make a theoretical contribution to understanding artificial intelligence/machine learning (AI/ML) in a naval fleet architecture to speed up the decision-making process and show commanders confidence in the predictions within a command and control (C2) headquarters afloat or ashore. Predictability means that models are reliable and data are representatively complete. The end state is merging the Future Knowledgebase System of Systems (FKSS) with AI/ML Engines to maximize system reliability and data availability for decision support. This knowledge architecture can offer a diffusion of ideas in an adaptive learning environment. The naval fleet unit will need to dynamically adapt its System of System (SoS) reliability and availability management methods with AI/ML agents. These analytic data problems involve three dimensions to meet the challenges—People, algorithms, and machines. The decision-makers can address overall risk management values, and the AI/ML algorithms can adjust to the individual machines and their data. The overall reliability and availability of the FKSS will be gauged by the ability to access individual systems when required to migrate authoritative data into one location or a few corresponding locations where AI/ML can act on it. The "gauge" is assisted by information sciences, data science, and risk management.


Maximizing Data Capabilities for Decision Making with Artificial Intelligence (AI) / Machine Learning (ML) in a Naval Future Knowledgebase System of Systems (FKSS)


**Title:** Course of Action Engineering   

**Moderator:**  Captain Scot Miller (Ret.), Naval Postgraduate School


               
        


  Course of Action Engineering - Q&A

technical paper

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Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

To spread awareness of current machine learning research relevant to Naval applications

To connect machine learning researchers with experts in military requirements

To build and strengthen collaborations within the defense research community


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NAML 2022

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop. The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

To spread awareness of current machine learning research relevant to Naval applications

To connect machine learning researchers with experts in military requirements

To build and strengthen collaborations within the defense research community



Don Brutzman

1

Presentations

Maximizing Data Capabilities for Decision Making with Artificial Intelligence (AI) / Machine Learning (ML) in a Naval Future Knowledgebase System of Systems (FKSS)

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