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Frequently Asked Questions (FAQs)

What is the "Multi-INT Research Initiatives at the Naval Postgraduate School" opportunity?

It is a Department of Defense research funding opportunity (NPS FOA 16 002) administered through the Office of Naval Research (ONR). The sponsor is the Naval Postgraduate School (NPS) Center for Multi-INT Studies (CMIS). The focus is forward-leaning research to advance intelligence, surveillance, and reconnaissance (ISR), especially where multiple intelligence sources (Multi-INT) must be fused into timely, actionable decisions.

Who is sponsoring and administering this program?

The sponsoring organization is the Naval Postgraduate School Center for Multi-INT Studies (CMIS). The effort is administered through the Office of Naval Research under the Department of Defense.

What is CMIS trying to accomplish with this program?

CMIS is aiming to fundamentally modernize how intelligence is collected, processed, and translated into decisions. The program is framed around reducing the limits of a slow, linear, human-labor-intensive intelligence cycle and replacing it with faster, more adaptive processes that keep up with continuous, multi-domain data and evolving adversary behaviors.

What problem is this funding opportunity trying to solve?

The opportunity responds to a practical operational gap: analysts, warfighters, and senior decision-makers increasingly need real-time, accurate, actionable intelligence, but the traditional intelligence cycle can be too linear and too dependent on manual effort. At the same time, modern operating environments produce data continuously across many domains, creating scale and complexity that exceed what humans can interpret quickly enough.

What kinds of research topics and capabilities are emphasized?

The description emphasizes cognitive and advanced computational approaches that accelerate and improve intelligence-cycle processes. It highlights capabilities such as decision support, situational awareness, sensemaking, inferencing, reasoning, and advanced visualization, especially where these methods can extract meaning from many data streams quickly and reduce reliance on slow, manual workflows.

Is this about replacing analysts, or about human-machine teaming?

The vision described keeps analysts and decision-makers in the loop. The automated process generates outputs for humans, and humans provide guidance and new information back into the system. The goal is to have machines handle more of the heavy lifting in fusion and interpretation while humans focus on judgment, oversight, and mission decisions.

What does "Multi-INT" mean in the context of this program?

Within this opportunity, Multi-INT refers to using multiple sources and types of intelligence data together (multi-source, multi-dimensional) and fusing them to support intelligence production and decision-making. The emphasis is on working across many streams of data rather than improving only one isolated sensor or single data type.

What is the long-term technical vision CMIS describes?

The long-term vision is an automated, closed-loop system for Multi-INT collection and analysis that can anticipate information needs, coordinate distributed sensors, and recommend actions. This includes linking analysis to collection strategy so the system not only interprets what is already known, but also drives what information should be collected next and how to collect it efficiently.

What domains are included in the program's cross-domain focus?

The opportunity explicitly calls out orchestration across "every domain," including cyber, human, terrestrial, air, sea, and space. This signals interest in cross-domain fusion and sensor tasking rather than a narrow focus confined to one environment.

What are the five functions in the automated Multi-INT loop described?

CMIS summarizes the future architecture as a five-function automated loop:

1. Automatically synthesize information about a target from large repositories of Multi-INT data.
2. Use target behavior models to support or refute hypotheses about activities based on synthesized evidence.
3. Perform information value calculations to determine what information would be most useful to obtain next.
4. Use efficient algorithms to orchestrate a diverse set of sensors to collect the next best information and increase overall intelligence value.
5. Keep analysts and decision-makers in the loop so they receive outputs and provide guidance and new information back into the system.

What does "information value" mean here?

In this solicitation, "information value" refers to calculations that prioritize what information should be collected next based on expected intelligence gain. In other words, the system is expected to help decide what collection would be most useful, rather than collecting everything or relying only on manual prioritization.

How does sensor orchestration fit into the program?

Sensor orchestration is a core part of the closed-loop concept. The opportunity describes algorithms that coordinate a diverse set of sensors to collect the next best information, with the intent of improving overall intelligence value. This suggests interest in methods that can task, coordinate, and optimize collection across distributed capabilities.

What type of funding instrument will be used?

The opportunity indicates awards may be made using either grants or cooperative agreements. That implies the government may expect varying levels of involvement depending on the specific project and instrument selected.

What does it mean that cooperative agreements may be used?

The listing notes cooperative agreements as a possible award type, which typically signals that there may be more government involvement in the work for some projects compared to a standard grant. The exact level of involvement would depend on the project and award structure.

What is the program area or classification for this opportunity?

It is positioned in the science and technology / research and development space and is identified with CFDA 12.300.

Who is eligible to apply?

Eligibility is listed broadly as "Others," with additional clarification referenced in the original notice. Based on the provided description, this suggests that non-traditional performers or organizations outside typical academic/government categories may be eligible, but the specific eligibility requirements would be defined in the full announcement.

When was the opportunity posted and when did it close?

The posting date was May 5, 2016. The closing date was June 30, 2016.

Is the award ceiling or expected number of awards provided?

No. The provided record does not specify an award ceiling or the expected number of awards. In such cases, applicants typically need to consult the full funding announcement for budget expectations and the likely scale of the program.

What kinds of outcomes is CMIS looking for from funded research?

Based on the description, CMIS is looking for transformational approaches that improve timeliness, reduce human workload, and produce intelligence outputs and collection decisions that are faster, smarter, and more adaptive than largely manual processes. The emphasis is on high-speed Multi-INT fusion, automated reasoning about targets, sensor management guided by information value, and strong decision-support outputs.

Does the opportunity emphasize real-time decision-making?

Yes. The motivation explicitly includes the need for intelligence that is real-time, accurate, and immediately actionable, with research aimed at accelerating intelligence-cycle processes so outputs can keep pace with operational demands.

Is the program focused only on analysis, or also on collection?

It includes both. The vision links analysis directly to collection strategy: the system interprets existing information, determines what should be collected next via information value calculations, and orchestrates sensors to collect that next best information.

What does "forward-leaning research" imply in this context?

In the context provided, it indicates an interest in innovative, next-generation approaches that move beyond incremental improvements, particularly approaches that modernize the intelligence cycle through advanced computational and cognitive methods.

What is meant by improving "sensemaking" and "advanced visualization"?

As described, these are capabilities intended to help extract meaning from many streams of data quickly. Sensemaking and visualization are positioned as ways to reduce manual burden and improve situational understanding so analysts and decision-makers can act faster and with better context.