STRONG Program Announcement W911NF-19-S-0001 Ammendment 1.pdf

ARL Strengthening Teamwork for Robust Operations in Novel Groups (STRONG)

I. OVERVIEW OF THE FUNDING OPPORTUNITY

A. REQUIRED OVERVIEW CONTENT

1. Federal Awarding Agency Name

2. Research Opportunity Title

3. Announcement Type

4. Funding Opportunity Number

5. Catalog of Federal Domestic Assistance (CFDA) Number(s)

6. Key Dates

B. ADDITIONAL OVERVIEW INFORMATION

II. DETAILED INFORMATION ABOUT THE FUNDING OPPORTUNITY

A. PROGRAM DESCRIPTION

1. ARL Strengthening Teamwork for Robust Operations in Novel Groups (STRONG) . 6

2. Collaboration

3. Proposal Intent

4. Research Timeline

5. Funding

B. AWARD INFORMATION

C. ELIGIBILITY INFORMATION

1. Eligible Applicants

2. Cost Sharing or Matching

D. APPLICATION AND SUBMISSION INFORMATION

1. Address to Request Application Package

2. Content and Format of Application Submission

3. Submission Dates and Times

E. APPLICATION REVIEW INFORMATION

1. Criteria

2. Review and Selection Process

3. Recipient Qualification

F. AWARD ADMINISTRATION INFORMATION

1. Award Notices

2. Administrative and National Policy Requirements

3. Reporting

G. AGENCY CONTACTS

H. PROTECTION OF HUMAN SUBJECTS

References:

I. OVERVIEW OF THE FUNDING OPPORTUNITY

A. REQUIRED OVERVIEW CONTENT

1. Federal Awarding Agency Name U.S. Army Research Laboratory, 2800 Powder Mill Road, Adelphi, MD 20783-1197

Issuing Acquisition Office U.S. Army Contracting Command – Aberdeen Proving Ground, Research Triangle Park (RTP) Division, 800 Park Office Drive, Suite #4229, Research Triangle Park, NC 27709

2. Research Opportunity Title

Strengthening Teamwork for Robust Operations in Novel Groups (STRONG)

3. Announcement Type Initial

4. Funding Opportunity Number

W911NF-19-S-0001

5. Catalog of Federal Domestic Assistance (CFDA) Number(s)

12.630 - "Basic, Applied, and Advanced Research in Science and Engineering"

6. Key Dates

The following is a summary of the events and dates associated with the STRONG Funding Opportunity:

EVENT ESTIMATED DATE/TIMEFRAME

Opportunity released October 2018 Opportunities Webinar 15 November 2018 Deadline for Questions on Funding Opportunity 30 November 2018 Proposals due for Cycle 1* 21 December 2018 Cycle 1 Awards* Feb2019 (Expected)

*The Key dates above delineate the timeline for proposal receipt and award related to Cycle 1 under this Funding Opportunity Announcement (FOA). See below for information on subsequent cycles.

B. ADDITIONAL OVERVIEW INFORMATION

Purpose: The future vision for the U.S. Army includes teams of humans and intelligent agents working together to accomplish missions. The U.S. Army Research Laboratory (ARL) has established this new collaborative program, Strengthening Teamwork for Robust Operations in Novel Groups (STRONG), with the goal of developing the foundation for enhanced teamwork within heterogeneous human-intelligent agent teams. This collaborative venture will bring together diverse, multidisciplinary expertise to support scientific breakthroughs relevant to specific and critical scientific questions that must be addressed to enable this future vision.

STRONG focuses directly on coordination and cooperation in human-agent teams via individualized and adaptive technologies. It has a specific long-term goal to identify and implement the fundamental research necessary to develop individualized, adaptive technologies that promote effective teamwork in novel groups of humans and intelligent agents. This effort addresses the teamwork (states and processes) that is critical to the future vision of human-agent teaming in the military. Decostanza et al.

(IEEE, 2018; https://brain.ieee.org/brain-storm/enhancing-human-agent-teaming/) provide a detailed vision and discussion of some of the scientific questions critical to achieving this goal. Importantly, this interactive paper also provides a public forum for commentary and feedback from the scientific community at large and will serve as a valuable resource for understanding the research objectives of this program.

STRONG addresses a critical objective within a broader Army goal to enable effective integration of Artificial Intelligence / Machine Learning (AI/ML) in the battlefield. This program has been developed in coordination with other related ARL-funded collaborative efforts (see descriptions of ARL collaborative alliances at https://www.arl.army.mil/www/default.cfm?page=93) and shares a common vision of highly collaborative academia-industry-government partnerships; however, it will be executed with a program model different than previous ARL Collaborative Research/Technology Alliances.

Specific components of the program are highlighted below:

STRONG will be executed through a series of eight annual program cycles (i.e., Cycles 1-8).

The FOA will be amended annually to identify a specific problem statement, or topic, for that specific Cycle. The topic for each Cycle will be chosen to systematically converge on the specific long-term program goal.

o Eight new topics (Cycles 1-8) are expected from FY19-FY26, with each topic focused on addressing a different scientific area within the scope of the broad research aims of STRONG. These topics will be carefully chosen based on both program achievements from the previous year and on scientific and technological advancements by the broader research community.

o For each topic, funding will be provided to those Recipients selected for 1 year under a cooperative agreement (CA) described as the “seedling” project.

o The Recipients of a “seedling” CA are then eligible to receive funding for a single optional extension of up to 3 years at the conclusion of the “seedling” project. The period of the performance of the option will be based on the research and available funding. It is envisioned that “seedling” Recipients will work with government researchers and/or other “seedling” Recipients to collaboratively develop a proposal for an optional extension to the initial seedling CAs. Opportunities for planning and enabling these collaborations in support of an option will be provided at the annual Summer Innovation Summits (see below), as well as via regular communication between “seedling” Recipients and government researchers.

Recipient participation in a yearly Summer Innovation Summit at one of the Center for Agent Soldier Teaming (CAST) Innovation Hubs will be REQUIRED.

Proposals from junior investigators (e.g., students, research fellows, and early-career researchers with less than 5 years past reception of their PhD or less than 5 years’ experience within the primary field of their organization) are appropriate under this opportunity.

The success of this multidisciplinary effort will require meaningful collaborative partnerships between government, academia, and industry to advance the science of human-agent teaming. The STRONG program incorporates new initiatives to grow and support an eco-system of high-quality, innovative researchers addressing scientific gaps critical to the Department of Defense. At the beginning of each annual Summer Innovation Summit, Recipients will be expected to demonstrate their scientific principles and approach to the community, providing evidence of progress toward scientific breakthroughs that support the criticality of the particular concept or approach to the specific topic. Over the course of each yearly Summer Innovation Summit, Recipients will be expected to coordinate their future research plans with complimentary ongoing or planned efforts executed by other Recipients and government researchers.

In other words, it is expected that the best methods or findings from individual “seedlings” will be leveraged to inform strategy and best practice approaches for subsequent future option proposals.

Following each annual Summit, 1-3 collaborative proposals will be selected for up to three additional years of effort being funded for each selected Recipient (with more details on the option process to be provided during “seedling” year).

Funding Cycles:

FY19 FY20 FY21 FY22 FY23 FY24 FY25 FY26 FY27 FY28 FY29

Proposal

Submissions

Cycle 1 B O O O DEC 2018

Cycle 2 B O O O SEP 2019

Cycle 3 B O O O SEP 2020

Cycle 4 B O O O SEP 2021

Cycle 5 B O O O SEP 2022

Cycle 6 B O O O SEP 2023

Cycle 7 B O O O SEP 2024

Cycle 8 B O O O SEP 2025

Note: B is for Base (“seedling”) period of Cooperative Agreement; O indicates 3-yr Option

The Cycle 1 Topic is described in this FOA. Future topics will be released annually as amendments to this FOA.

Award Instrument: This Funding Opportunity is expected to result in the award of multiple seedling cooperative agreements (CA) during each Cycle as defined at 31 U.S.C. 6305 for the execution of the program. The CA is used to enter into a relationship:

a. The principal purpose of which is to transfer a thing of value to the Recipient to carry out a public purpose of support or stimulation authorized by a law or the United States, rather than to acquire property or services for the Federal Government’s direct benefit or use.

b. Substantial involvement is expected between the Federal Government and the Recipient when carrying out the activity contemplated by the CA.

c. No fee or profit is allowed

Structure of Award: The CAs will consist of an initial 12-month Base award that will be executed and considered as “seedling” CAs. Each seedling CA will provide for the potential for exercising an option, adding up to three more years to the base award, as outlined in the table above. This proposed additional effort may be scoped for one to three years based on its objectives, will be collaboratively developed with Government scientists during the period of performance of the seedling CA, and will be presented as part of the outcome of collaborations during the annual Summer Innovation Summits (described below).

Proposal Submission: The application process (see PART II.D) consists of proposal submissions from applicants for each Cycle under this FOA. Applicants should note that there are page limitations and other requirements associated with the submission process. Submissions in connection with this FOA are due by the date and time specified in PART II.D.3. FOA amendments for future topics will include the submission requirements for those submissions. The Government’s decision to award a seedling CA will be based upon the evaluation results of the proposal submission.

Period of Performance: The CA Awards made as a result of this FOA will provide for a period of performance of one year, with the potential to add up to three additional years to the period of performance at the discretion of the Government.

Place of Performance: There is no limitation on the place of performance, except for Recipient participation in the annual Summer Innovation Summits. The initial Summit will take place in Burlington, MA and in the surrounding areas in the summer of 2019 and then the Summits thereafter will rotate between ARL CAST Innovation Hub locations (e.g., Aberdeen Proving Ground, MD; greater Boston, MA area; TBD) Further details on this requirement are outlined in PART II.A.2 (Collaboration).

Funding: This FOA is issued subject to the availability of funds. ARL has submitted the requisite documents to request funding for the period covered by the program. However, Applicants are reminded that this request is subject to Presidential, Congressional and Departmental approval. Funding levels specified in this Funding Opportunity are estimated funding levels and are for proposal preparation purposes only; actual funding levels of the CAs will be updated annually as part of the federal appropriation process.

Profit/Fee: Profit/fee is not permitted under the CA.

Cost Sharing: Cost sharing is not required under this FOA.

Evaluation and Award: Evaluation and Award in connection with this FOA will be performed in accordance with PART II.E. Proposals that are in compliance with the requirements of the FOA will be evaluated in accordance with merit-based, competitive procedures. These procedures will include evaluation factors and an adjectival and color rating system. A review team, consisting of a qualified group of scientists and managers will evaluate the compliant Proposals and provide the results of that evaluation to the decision-maker for the Government.

Eligibility. Eligible applicants under this FOA include institutions of higher education, nonprofit organizations, and for-profit organizations (i.e., large and small businesses) for scientific research in the knowledge domains outlined throughout this Funding Opportunity. Federally Funded Research and Development Centers (FFRDC) may propose as well, with effort as allowed by their sponsoring agency and in accordance with their sponsoring agency policy. Proposals will be evaluated only if they are for fundamental scientific study and experimentation directed toward advancing the scientific state of the art or increasing basic knowledge and understanding. Additional eligibility information is provided in

PART II.C.

Opportunity Webinar: ARL will host an opportunity webinar on 15 November 2018. A link to the webinar will be posted on the STRONG Program website at https://www.arl.army.mil/strong.

Contact Information. Outside of questions posed at the Opportunity Webinar, all questions or comments concerning this FOA shall be submitted to the Government through the STRONG Program website at https://www.arl.army.mil/strong. Comments or questions submitted should be concise and to the point. In addition, the relevant part and paragraph of the FOA to which a comment or question pertains must be referenced. Responses to non-proprietary questions received will be posted to the STRONG Program website under the “General Information/Questions & Answers" section for the benefit of all interested parties. All clearly identified and marked proprietary questions posed will be responded to via an individual email response, not posted to the STRONG Program website. Applicants are encouraged to submit questions as early as possible. The deadline for submission of questions which will be answered under this FOA is 30 November 2018. Any answers provided to questions do not change the requirements of this FOA. Future amendments to this FOA, including new cycle topics, will be issued via an amended FOA posted in grants.gov.

II. DETAILED INFORMATION ABOUT THE FUNDING OPPORTUNITY

A. PROGRAM DESCRIPTION

1. ARL Strengthening Teamwork for Robust Operations in Novel Groups (STRONG)

The recent acceleration in the emergence and widespread application of artificial intelligence and machine learning (AI/ML) is leading to a fundamental revolution in the way that society functions on all levels across the globe. Whether in wrist-worn sleep and activity monitors, online shopping carts, “smart” mobile devices, or even in our vehicles, AI/ML-enabled intelligent agents are quickly becoming ubiquitous and, as such, fundamental to life experience in the developed world. With ever-more intelligent technological capabilities and particularly the increasing availability, modes, and transmissibility of information that can reshape our understanding of the global context and human action within it, the U.S. Army Research Laboratory has established a new collaborative, basic research program (STRONG) with the intent of providing a foundation for enhanced teamwork within heterogeneous human-intelligent agent teams. This new collaborative venture will bring together diverse, multidisciplinary expertise to support scientific breakthroughs within specific, critical scientific questions that must be addressed to enable this future vision.

Background

As the vision for the Internet of Things and Artificial Intelligence promises a world of interconnected devices that anticipate and respond to our needs, we can expect future military teams to be equipped with an array of intelligent, autonomous, and networked agents that perform core team functions, anticipate and respond to the needs of the team, and make decisions both in coordination with their human teammates.

This will differ fundamentally from the human-centered team concepts on which military doctrine and organizational psychology are currently built. We are expectedly rethinking the mechanisms that we employ to train personnel and perform complex team operations in the U.S. Army. At present, military teams train and operate with a host of advanced technologies, but at its core, technology endows human team members with greater individual capabilities and does not necessarily enhance or fundamentally change the short- and long-term emergent properties of team performance. However, the future vision for human-agent teaming in the Army will require close cooperation, coordination, and communication between ad-hoc teams of humans and agents (e.g., robots, intelligent assistants, and intelligent sensors acting as discrete teammates rather than as tools). Further, both Soldiers and intelligent agents (both envisioned to have varied levels of training, experience, and operational capabilities and roles) will likely be required to adapt to new missions on demand. This future concept of human-agent teaming assumes:

(1) First, human capabilities within the environment will continue to be necessary. The specific capabilities required of humans will change from what they are today, but technology will not replace humans completely.

(2) Second, the roles of humans and the nature of the interactions they have with intelligent agents will change. The concept of technology being a tool for humans will be replaced by technology as mentored actors in the environment, teammates with unique non-human skills, and technology that augments fundamental human capabilities.

(3) Third, the training required for humans to be effective will change dramatically. Training will have to enable humans to handle the dynamic and rapid evolution of technology as well as the shift in critical analysis and action from humans to intelligent technology.

Advancements across many different domains are considered critical to this future human-agent teaming vision. Piekarski et al. (2016) document many of the challenges from an intelligent systems perspective, including: how to integrate and control large autonomous teams with varying levels of autonomy and intelligence across spatially and temporally distributed systems; how to combine autonomous agents, sensors, and tactical super-computing to establish distributed networked intelligent systems; and how to develop methods for heterogeneous teams to carry out tasks under dynamic and varying conditions.

Similarly, Suri et al. (2016) describe research challenges related to fundamental understanding of how to learn and devise complex models of the Internet of Battlefield Things (IoBT), including goals, networks, information, and analytics that enable intelligent command and control, and battlefield services. In 2017, the Army Research Laboratory began two large-scale collaborative research programs (IoBT CRA and DCIST CRA) to address these challenges (see https://www.arl.army.mil/www/default.cfm?page=532 for more details.

Neither of these current efforts specifically target solutions to enhance human strengths and mitigate human weaknesses, nor do they directly address development of the inherent teamwork (states and processes) between humans and intelligent agents that is critical to realize the future Army vision. STRONG focuses on a specific long-term goal to provide the fundamental research necessary to develop individualized, adaptive technologies that promote effective teamwork in novel groups of humans and intelligent agents.

What do we mean by teamwork? Many researchers have argued that team performance is a multilevel process that includes both individual taskwork and individual- and team-level teamwork processes (Kozlowski and Klein, 2000; Salas et al., 2007). Marks et al. (2001) provided definitions of taskwork and teamwork to distinguish the two, suggesting that, “taskwork represents what it is that teams are doing, whereas teamwork describes how they are doing it with each other” (p. 357, emphasis added).

When we refer to human-agent teaming and human-agent teamwork, we are focused on the team-level emergent properties, including states and processes, that influence performance and effectiveness (e.g., cohesion, shared mental models, shared situational awareness, coordination, and communication), rather than individual taskwork.

What do we mean by technology? Agent? We expect future teams to be composed of humans as well as distributed sensors, robots, autonomous ground and air vehicles, intelligent assistants, and other advanced technologies that can perform taskwork as part of the larger team. Hence, an agent can perform interdependent taskwork. We reserve the term technology for those devices, software, protocols, and other interventions that target the members of the team with the goal of improving team processes. It is entirely possible that a technology will both perform taskwork and provide interventions that target team processes. We use the term technology when referring to its role as assisting in team performance as opposed to satisfying its role in the team (i.e., completing its assigned task work).

Technologies of the future should be individualized and adaptive. For over a century, military technologies and doctrine have prioritized the interchangeability of operators (see Howard, 1961).

Although this leads to robust performance, it also limits system capabilities and likely constrains high-performing individuals from fully utilizing their own and the system’s capabilities. Future technologies need to be adaptive and individualized, accounting for individuals’ capabilities and limitations in real-time to achieve greater performance, especially in complex environments under operational tempos that may be faster than possible through human capabilities alone. By allowing individual agents to behave in manners that are consistent with their own strengths rather than imposing uniform behavioral requirements or constraints, individual performance should be dramatically improved. Shifting to this paradigm will also enable technological solutions to target particular individual capabilities that improve team-level properties and performance.

Given the above context, this program focuses on science and technology to enable the interactions and interdependencies between heterogeneous members of human-agent teams, and specifically, on influencing individual team members, human or agent, to enhance positive emergent team properties and performance.

Within this program, we anticipate the need for research in three broad, intertwined areas that frame the technical and scientific challenges: (1) Developing theory and models to characterize the linked relationships between individual team member dynamics and the emergent, dynamic properties of human-agent teams; (2) Systems-based approaches to dynamically individualize and adapt technologies to optimize human-agent team performance; and (3) Approaches for training and developing individuals and groups that account for and exploit unique learning and adaptation among human and intelligent agents to enable enhanced human-agent team performance over time.

Critically, our perspective is not solely focused on the differences between individuals. Rather, we expect that detecting, understanding, and predicting intra-individual performance fluctuations will enable the largest innovations for technology that can adapt to the real-time needs of the team. These intra-individual performance fluctuations occur at multiple time scales in both humans and agents. Within the STRONG program, we extend the focus on individual differences for individualized performance prediction, and we ask how individual dynamics and variability can be exploited to improve team-level properties and performance in heterogeneous, human-agent teams well beyond the modern state-of-the-art.

Cycle 1: Theory development and Team-Level Processes

We have focused this announcement (Cycle 1) on fundamental research aimed at theories of team-level processes for heterogeneous human-agent teams. Critically, the Cycle 1 topic research must provide the building blocks for identifying and developing the Cycle 2-8 research topics in support of STRONG’s overall long-term goal. Specifically, it must provide the building blocks for these potential future topic areas:

Theories linking individual dynamics to emergent processes in human-agent teams Models bridging dynamic, continuous individual and group attributes, emergent team behaviors, and team performance Predicting and leveraging individual performance fluctuations for improved overall team performance

When human teams fail, breakdowns are commonly due to problems with team states and processes:

insufficient communications, misunderstanding of team goals, undefined team responsibilities, lack of shared mental models, and conflict; as examples (Kohn et al., 2000; Salas et al., 2007). Team-focused training and development literature suggests that the best human teams can overcome external demands (e.g., distributed environments, lack of resources, time pressures) and some individual performance problems by implementing effective team processes that may not always lead to superior performance on any given task by any specific individual, but that will achieve superior overall team performance over time (Weaver et al., 2014). However, in teams composed of humans, intelligent software agents, embodied agents, and networked sensors, emergent complexities may arise that are not necessarily predictable based on our current comprehension of team processes. Considering cognitive and behavioral processes such as decision-making and coordination, humans and agents will be working in disparate dimensions (time, space, world views, representations, mental models, etc.), yet need to seamlessly synchronize for collective action. For example, intelligent agents will process information, reason, and make decisions at scales beyond that of humans in both time and magnitude; and yet, we will want to include humans in the decision-making loop for many, if not most, decisions. Similarly, intelligent agents will learn and adapt far more rapidly than their human counterparts, but may possess less flexibility and range in what they can learn.

Clearly, we need methods and technologies to capitalize on the individual advantages of both humans and agents while simultaneously enhancing the performance of the collective.

Not only are methods needed to bridge diverse capabilities, processes, and beliefs, but much of what we currently know about critical states and processes in human teams may not be applicable. The notion of a shared mental model among humans and intelligent agents raises significant scientific and philosophical questions. Shared understanding of team responsibilities and goals among humans and intelligent agents, as it is practiced in human teams, assumes intelligent agents with human-like intelligence. However, non-human teammates will likely span the spectrum of machine intelligence — from passive sensors to advanced, adaptive machine learning algorithms.

Breakthroughs in representation learning and explainability should facilitate human understanding of machine reasoning, but are shared mental models like those targeted in human teams the right approach to human-agent teaming? The nature of these emergent properties is fundamentally different than our conceptualization today, and it is perhaps naïve to assume that human-agent team cohesion, coordination, and collective performance will develop in ways similar to human teams without targeted scientific focus.

Therefore, this problem space demands research to identify and characterize the critical states and processes for effective performance in human-agent teams. In identifying and characterizing these critical states, understanding how individual dynamics influence these emergent properties is critical to the broader goal of utilizing individualized and adaptive technologies to elicit resilient, emergent processes in human-agent teams.

Specifically, proposed research should seek innovative solutions to advance the development and validation of theoretical principles related to identifying, measuring, understanding, and predicting the team-level states and processes that are critical for effective group-level performance in heterogeneous human-agent teams. Below are several related core scientific questions addressing interactions between humans and agents that may be addressed in the proposed work. This list is not expected to be comprehensive and Applicants may offer additional critical questions related to the Cycle 1 focus and its linkages to STRONG’s long-term program goal.

(1) Shared mental models underlie the effective communication and coordination of human teams, and similar concepts have emerged in multi-agent systems both organically and by inspiration from human teaming. In complex teams of the future, will it be necessary to maintain a shared mental model amongst teams of humans and intelligent agents? If so, we must understand how to operationalize “shared” mental models in these complex teams. Research may ask how human-agent teams will develop, manage, and communicate shared mental models of the problem, environment, and the states and intentions of other team members in order to facilitate rapid mission planning and adaptation.

(2) Effective teams capitalize on a rich knowledge of each other’s strengths, weaknesses, and patterned behavior to inform role assignment predict each other’s performance in specific situations. For example, in a future human-agent teaming scenario wherein intelligent agents can readily download new behavior models, no coherent team may exist for longer than a single mission or sub-goal.

Research is thus needed to define necessary and sufficient mechanisms that can achieve the effect of rapid rapport development and effective communication with new team members. What are the requirements of anticipating actions or recognizing strengths and weaknesses of new members? How do we develop intuitive, common languages (e.g., incorporating body language, facial expressions, tones of voice, or even physiological measures) in human-agent teams? Research questions may focus on identifying which aspects of rapport-building and trust are most critical in evolving heterogeneous teams as well as how to develop these constructs of interaction in both humans and agents.

(3) A rich body of literature connects particular teamwork processes such as communication, shared mental models, and coordination with effective performance in human teams. Studies are needed to determine whether current and proposed models of the critical emergent team processes will generalize to human-agent teams. Will the same emergent team processes be critical in human-agent teams, or will other novel team processes emerge? How will emergent team properties (states and processes) be validated and measured? What is the most effective means of communication in order to facilitate coordination and optimal team performance, especially taking into account dynamic operational environments (darkness, battlefield noise, radio loss), state-related constraints (fatigue, attention, equipment failure), and changing task demands?

While proposed efforts need to focus on the specific topic within this Funding Opportunity: research proposals MUST align with the broader, long-term program goals of optimizing a system of interdependent agents through individualized and adaptive technological and training solutions aimed at improving critical team-level properties and group performance. A successful research project will lay the scientific foundations for enhanced human-agent teaming using individualized, adaptive approaches by combining new developments in theory, computationally efficient modeling techniques, empirically driven model development, and principled experimental validation.

2. Collaboration

This program continues the ARL concept of creating collaborative relationships between ARL and its partners. Experience has shown that persistent collaboration across government, academic, and industry performers enhances innovation and has a high return on investment. Therefore, collaboration between Awardees and Government researchers is integral to the execution and success of the program. It is ARL's fundamental belief that work conducted under the STRONG Program cannot be successful either in whole or in part without collaboration. Creation of an environment that is conducive to collaboration is therefore a critical element in establishing the program. ARL will specifically fund internal researchers to foster direct, highly collaborative partnerships between STRONG Recipients and the Government. ARL will shape its mission program to maximize synergies with the STRONG research strategy and the annual STRONG Cycles, thus supporting a direct and continuing collaboration across the program. The Government may also leverage and/or integrate other interested Government agencies (and funding where appropriate).

This section describes potential avenues to collaborate under the STRONG program. The implementation of the collaboration with ARL will be through the CA.

a. Participation in CAST Innovation Hubs

A significant goal of this effort will be to create a critical mass of collaborating scientists and engineers focused on solving STRONG research challenges outlined within the scope of the program. This intellectual synergy is also expected to include sharing equipment, personnel and facilities to promote efficiency and enhance collaboration.

The ARL Center for Agent-Soldier Teaming

Research coordination and collaboration within the STRONG program, as well as within other ARL internal human-agent teaming research programs, will be facilitated through the Center for Agent-Solder Teaming (CAST; https://www.arl.army.mil/CAST). The CAST is a collaborative nexus where basic and applied researchers will create new theories, methods, and technologies to enable heterogeneous groups of humans and intelligent agents to team as dynamically as units of highly trained Soldiers do today. Using a combination of physical and virtual spaces, the CAST is designed to co-locate and integrate highly invested and engaged researchers, novice and expert alike, from across the spectrum of science and engineering related to human-agent teaming. It is expected that successful research teams may include, but not be limited to, agile and adaptive mixtures of experts in human sciences (e.g., social, cognitive, physiological) and intelligent systems (e.g., robotics, artificial intelligence, machine learning). Such collaborative teams may be formed among proposers or through planned collaborations with ARL investigators and engineers within the CAST.

Currently, CAST comprises two core innovation hubs: CAST-APG includes an integrated set of laboratories at the Aberdeen Proving Ground (APG) near Baltimore, Maryland; CAST-Northeast at ARL Northeast is comprised of government, university, and industry partnerships in Boston, MA and the surrounding areas. Both hubs provide essential tools for fostering innovation among teams of ARL researchers and participants in the STRONG program. Importantly, the CAST creates a network of online and physical resources for the formation of tight collaborations and alignment of research agendas with ongoing programs within human-agent teaming; therefore, it is critical that the proposed research will be formulated in anticipation of direct collaborations with ARL researchers and programs.

ARL recognizes that an important element of collaboration is the advancement, education and rotation of research staff through short-term temporary assignments. Staff rotations may be undertaken as part of this program to foster and facilitate collaborative research where face-to-face interaction is advantageous, to enable a researcher to utilize unique facilities, to enable STRONG personnel to obtain specialized training or experience and to facilitate the exchange of research results. In addition, this exchange, or cross-fertilization, of personnel will provide ARL partners with insight into Army-unique requirements and will provide Government personnel with insight into state-of-the-art research and commercial practices and/or the opportunity to pursue fundamental research with noted researchers.

At a minimum, proposals should include participation in the Summer Innovation Summit at the CAST Innovation Hub by at least one individual of each CA awarded. Costs associated with the Summit participation should be identified in the budget. All salary and travel costs associated with the rotation of Government personnel will be borne by the Government. All other salary and travel costs associated with staff rotations of STRONG performers may be funded under the CA.

b) Summer Innovation Summit

To achieve collaborative STRONG program goals, a yearly Summer Innovation Summit will be held. Each summer, the Summer Summit will be 4-8 weeks in length and targeted for graduate student, post-doc, early career scientist and engineer participation of each Recipient with support from senior faculty or industry representatives. ARL leadership, Government STRONG project collaborators, other government stakeholders, and industry partners will also attend, and participation will be encouraged from a broad community interested in the STRONG program goals. The location of the Summer Innovation Summit will rotate between the CAST Innovation Hubs, with the summer of 2019 expected to be held in Burlington, MA for 5 weeks from July 9th through August 10th. While attendance for the entirety of the multi-week Summer Summit is not required of all individuals who are members of a Recipient’s research team, planned participation by the Recipient throughout the entirety of the Summer Summit by AT LEAST one individual of each Recipient research team is required. While we expect attendance throughout the entirety of the Summit by at least one individual of each Recipient research team, we encourage additional participation by the Recipient teams and can accommodate multiple personnel and schedules, with emphasis placed on the importance of successfully presenting evidence of progress toward scientific breakthroughs as a result of each seedling CA, and for supporting the 3-yr option determination. The Summer Summit is expected to add critical value to the Recipient research teams and transition opportunities through the planned activities. Consistency in attendance by at least one individual of a Recipient research team will be critical to building collaborative partnerships, successful demonstrations, and transition opportunities. The planned participation by one or more individuals on the Recipient research team should be documented in the proposal.

One purpose of the Summer Innovation Summit is to provide an opportunity for Recipients of seedling CAs to work collaboratively to develop follow-on option proposals. The Summer Innovation Summit will start with Recipients demonstrating, with prototypes when possible, their initial concept, scientific approach, and accomplishments to date. A daily program will combine knowledge-building, brainstorming, technology/prototype development, and dedicated time and resources to conduct research, with the goal of quickly translating research into products that can transition into multiple environments. The Summer Innovation Summit is expected to culminate in collaboratively developed follow-on efforts, with proposed concepts and approaches demonstrated to a review panel. Full proposals for follow-on efforts (Option) will be submitted after the completion of the Summer Innovation Summit. Specific details for the submission of the follow-on proposals and evaluation criteria will be provided to the seedling Recipients during the course of their seedling award and prior to the Summer Innovation Summit.

The following description is intended to provide a vision of the Summer Innovation Summit activities for Summer 2019 for planning purposes, but does not constitute a finalized plan by the government. In addition to space and resources for developing and executing research aligned with the STRONG program, ARL is developing an agenda that includes some combination of the following activities: teaching seminars mixing academic, industry, and Army perspectives, focused on innovative practices and successful transition (e.g. military, business start-up); Army science planning and strategy development; Hack-a-thons with quick-solution challenges and mixed teams; brainstorming of research applications and development of transitions; development of scientific demonstrations and an Industry Day (a day of demonstrations targeted toward industry stakeholders designed to develop multiple transition pathways); and planning and development of new “seedling” proposals. With that in mind, the following is a notional timeline of events being planned for Summer of 2019:

Notional Timeline Week 1 (8-12 July): Demonstrations of initial concept and approach from all Cycle 1

Awardees; orientation, team-building Week 2 (15-19 July): Collaboration building week + research Week 3 (22-26 July): Army science planning and strategy week + research Week 4 (29 July – 2 Aug): Application Brainstorming Week / Hackathon + research Week 5 (5-9 August): Demonstrations of proposed follow-on efforts, Industry Day

Investigator Experience

ARL strategically designed the Summer Innovation Summit to target development of junior investigators to build onto the ecosystem of researchers working on questions relative to Army priorities. Aligned with this vision, ARL recognizes that a Recipient’s junior investigators may constitute the majority of researchers attending the Summer Innovation Summit for its entirety.

Where applicable, the Recipient’s senior faculty members and/or mentors shall participate in particularly relevant portions of the Summer Innovation Summit (e.g., supporting demonstrations, follow-on effort development, mentorship, lectures, etc.). All proposed efforts, whether led by a junior or senior investigator, must include a plan for attendance and support of the Summer Innovation Summit as described above.

Investigators at various levels of hierarchy (e.g., undergraduate students, graduate students, post-doctoral fellows, research associates; Assistant, Associate, Full, or Distinguished Professors, and comparable industry classifications) are encouraged to submit proposals as Principal Investigators within the STRONG program. To encourage diversity and enable the review team to select a range of participants, proposals must be designated as originating from either Junior or Senior Investigators.

Junior Investigators: Junior investigators consist of students, research fellows, and early-career faculty who are less than 5 years past reception of PhD or equivalent doctoral degree at the time of application submission. In the case of industry and non-profit organizations, this includes representatives who have less than five years of experience within the primary field of the organization.

Senior Investigators: Senior investigators consist of faculty and staff who are five years past reception of PhD or equivalent doctoral degree at the time of application submission. In the case of industry and non-profit organizations, this includes representatives whom have more than five years of experience within the primary field of the organization.

3. Proposal Intent

It is the intent of this FOA to solicit the most creative, innovative, and flexible approaches to the ultimate goal of generating and exploiting research to solve pressing research gaps and issues impacting both the military and commercial sectors. This FOA seeks Proposals which will result in the award of multiple CAs. In response to the Funding Opportunity, applicants will be required to provide evidence of the following in their proposal:

Formulate a basic research project that clearly demonstrates innovative, detailed, and substantive scientific plans to address the specific scientific challenge articulated in the Cycle 1 Topic Announcement, while aligning with the goals of the STRONG program. Focus should be placed on the goals you aim to accomplish in a 12-month seedling, with a brief notional concept of how this initial research could feed into a larger, potential 3-year effort in collaboration with government scientists and/or other seedling Recipients (focused on research goals and outcomes, rather than specific collaborators). Sufficient resources should be allocated to make progress in both science and forming effective collaborations within a 12-month period.

Identify a plan for attendance at the Summer Innovation Summit and any additional expected interactions at CAST. This could include a statement regarding potential collaborative partnerships with ARL programs or personnel based on interests defined on the CAST website and could include proposed staff rotations to a CAST Innovation Hub.

Present the experience, qualifications, and availability of the scientific staff and the quality and relevance of research facilities.

The research proposed and performed must comply with the definition for basic (6.1) research as outlined in the DoD Financial Management Regulation (FMR), Volume 2B, Chapter 5 as follows:

This announcement is for basic (6.1) research, which is defined as “systematic study directed toward greater knowledge or understanding of the fundamental aspects of phenomena and of observable facts without specific applications toward processes or products in mind.” (DoD 7000.14-R)

This announcement is NOT for applied (6.2) research, which is defined as “systematic study to understand the means to meet a recognized and specific need” and includes the “expansion and application of knowledge to develop useful materials, devices, and systems or methods.” (DoD 7000.14-R)

4. Research Timeline

The CAs will consist of an initial 12-month Base award that will be executed and considered as “seedling CAs.” Each seedling CA will provide for the potential of adding up to three more years to the CA period of performance. It is envisioned that the additional effort, up to three years, will be collaboratively developed with Government scientists and potentially other Recipients of “seedlings” during the subject Cycle (i.e., the 12-month period of performance of the seedling). The proposed effort and timeline for completion of an option (not to exceed three years) will be presented as part of the outcome of collaborations during the Summer Innovation Summit (described above), and followed by a written proposal for the option due following the Summer Innovation Summit.

Factors influencing the Government’s decision to fund further years of the research project will include:

technical merit of the proposed science, the potential for the proposed science to serve as a building block for the future topics of the STRONG program, performance and collaboration throughout the first year (seedling) of the CA, participation in the Summer Innovation Summit, and collaborative development of the proposal. Specific criteria will include: (1) demonstration of scientific accomplishments at the beginning of the Summer Summit, (2) evaluation of a written proposal and demonstration of proposed follow-on at Summer Summit, (3) relevance of the work to ARL, and (4) collaboration. It is anticipated that Recipients on multiple CAs may come together to propose collaborative follow-on efforts, along with research partners from the government.

More specific details regarding the follow-on proposals, including requirements, timelines, and evaluation criteria will be provided after award of the seedling.

5. Funding

Funding for most seedling project efforts will range from $50,000 to $100,000. Award of 10-15 seedling CAs is expected during each yearly cycle.

Funding for additional years beyond the seedling CA is expected to be larger in scope than the seedling CA. Additional efforts may be added for up to 3 years ranging between $350,000 and $500,000 per year.

It is anticipated that multiple Recipients may come together to collaboratively propose a follow-on effort with Government partners. Recipients may also bring additional entities (as subawardees) into proposed follow-on efforts that were not awarded as part of the CA initially based on the direction of their follow-on proposal.

B. AWARD INFORMATION

Multiple CAs will be awarded from this FOA. The Applicants selected for award will be notified by the Grants Officer or his/her designee telephonically or via email. The CA award is not official until the Recipient has received the award signed by the Grants Officer.

CAs for Institutions of Higher Education and nonprofit organizations are primarily governed by the following:

a. Federal statutes

b. Federal regulations

c. 2 CFR Part 200, as modified and supplemented by DoD's interim implementation found at 2 CFR Part

The following websites may be accessed to obtain an electronic copy of the governing regulations and guidance:

- FAR, DFARS, and AFARS: http://farsite.hill.af.mil/

- Code of Federal Regulations: http://www.ecfr.gov

- DoD Research and Development General Terms and Conditions JULY 2018

- ACC-APG-RTP Division Assistance, Research General Terms and Conditions dated

AUGUST 2016

C. ELIGIBILITY INFORMATION

1. Eligible Applicants

It is our goal for the program to include a diverse group of Applicants with varied long-term interests. During performance, it is envisioned that there will be two primary categories of participants from an Awardee (junior investigators and senior investigators, defined above), based upon their experience and time within their respective fields. Participants may be institutions of higher education, an industrial company, or non-profit organization.