Artificial Intelligence (AI)-based C2 Digital Assistant
Navy SBIR 2016.2 - Topic N162-074
NAVAIR - Mr. Jeffrey Kent - [email protected]
Opens: May 23, 2016 - Closes: June 22, 2016

TITLE: Artificial Intelligence (AI)-based C2 Digital Assistant

TECHNOLOGY AREA(S): Information Systems


OBJECTIVE: The objective is to develop an artificial intelligence (AI)-based Command and Control (C2) digital assistant that uses advanced computing techniques such as machine learning and natural language processing to provide answers to complex mission-specific questions to enhance battlespace decision making.

DESCRIPTION: The Marine Corps seeks to leverage advanced artificial intelligence (AI) technologies to reduce information overload, improve situational awareness (SA) and collaboration, and aid in Commander decision-making. The cognitive demands of future network-centric forces are overwhelming and commanders often get “caught in the weeds” and suffer from the glare of information. Intelligent assistants such as Apple’s Siri, Google Now, or Facebook’s “M” are commonplace in commercial industry yet similar products do not exist for military commanders tasked with managing an increasingly complex battlespace. New “big data” computing techniques such as predictive analytics, deep machine learning, distributed rules engines, and real-time contextual search can significantly ease the information burden and enable more effective and efficient decision making. These computing techniques not only identify patterns across multiple data sets but they recommend courses of action and evaluate proposed actions.

The aim of AI techniques embedded in an intelligent decision support system such as the proposed Command and Control (C2) digital assistant is to enable computer automation while emulating human capabilities as closely as possible.

The C2 digital assistant is envisioned to be integrated into the Common Aviation Command and Control System (CAC2S), an Acquisition Category I (ACAT I), Major Automated Information System (MAIS) that modernizes the air command and control suite in support of the Marine Aircraft Wings. The program replaces and modernizes the currently fielded, stove piped, and rapidly becoming obsolete aviation C2 equipment and facilities that support the Marine Air-Ground Task Force in Joint and combined air operations today. The Program received a positive Milestone C Decision in February 2015 and is ready to enter IOT&E in April 2016. The C2 digital assistant enhances the Command Tools function of CAC2S.

The AI-based C2 digital assistant will be a secure, open architecture system that runs continuously in the background and learns from its environment. It will utilize open-source libraries, software development kits (SDKs), and application programming interfaces (APIs) to the greatest extent possible and employ well-defined, well-documented interfaces to maximize modularity and extensibility. It will be capable of interpreting ad hoc natural language queries with minimal training and learn progressively as historical behaviors of both friendly and hostile forces are observed over time. By searching through vast troves of persistent unstructured data, the AI-based C2 digital assistant will greatly improve warfighting outcomes and enable commanders to compose “what if’s” based on intelligence information, local and remote sensor data, logistics and weapons information, and battle damage assessment activities. For example, disparate radio frequency emissions scattered across the battlefield may indicate the presence of an Integrated Air Defense System (IADS) and pose a threat to aviation assets. Using the C2 digital assistant to query previously detected RF emissions, the results will expose the presence of IADS assets and alter the Commander to apply appropriate action.

PHASE I: The small business will develop a concept for a high-level information architecture and componentized system design to meet the requirements for the AI-based C2 digital assistant described above. The company will document the feasibility and limitations of the digital assistant based on research and controlled testing of underlying concepts. The small business will provide a Phase II development plan with performance goals, key technical milestones, and risk reduction activities.

PHASE II: Based on the results of Phase I and the Phase II development plan, the company will develop a scaled prototype of the C2 digital assistant for evaluation and testing. The prototype will be evaluated to determine its capability in meeting the performance goals defined in the Phase II development plan and its ability to assist with efficient and effective decision making in a tactical environment. System performance will be demonstrated through prototype evaluation, modeling and simulation, and use case analysis. Phase II will be classified to the SECRET level. Battlefield data such as Tactical Digital Information Links (TADIL), sensor data, composite tracking data, and tactical intelligence information are examples of data that a C2 digital assistant will evaluate and assess. Testing is envisioned to be part of CAC2S Developmental Testing and Follow-on Operational Test and Evaluations at the Weapons and Tactics Instructor Courses in Yuma, AZ. Evaluation results will be used to refine the prototype implementation into an initial design that will meet Marine Corps requirements. The company will prepare a Phase III development plan to transition the technology to Marine Corps use.

PHASE III DUAL USE APPLICATIONS: If Phase II is successful, the small business will be expected to support transitioning the technology for Marine Corps use in operational command posts and C2 agencies. The company will develop and integrate a full-scale AI-based C2 digital assistant for evaluation to determine its effectiveness in an operationally relevant environment. The company will provide test and validation support to certify and qualify the system for integration into C2 systems such as the Common Aviation Command and Control System (CAC2S). Private Sector Commercial Potential: The potential for commercial application of an extensible AI-based digital assistant is high. Possible avenues for employment include search and rescue, first responder applications, law enforcement, homeland security, special operations, cyber defense, and Internet of Things (IoT) applications for consumers and businesses.


  • Common Aviation Command and Control System Overview.
  • Air Command and Control and Sensor Netting Overview.
  • Non-Deterministic Policies in Markov Decision Processes; Fard and Pineau, 2011.
  • Large Scale Deep Learning; Jeffrey Dean, 2014.
  • Facebook AI Research.

KEYWORDS: Artificial Intelligence; Decision Aid; Big Data; Machine Learning; Command and Control

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