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SAMDAILY.US - ISSUE OF OCTOBER 25, 2020 SAM #6905
SOLICITATION NOTICE

A -- Stratagem: Applying State-of-the-Art Artificial Intelligence and Machine Learning Approaches to Air Battle Management

Notice Date
10/23/2020 4:58:48 AM
 
Notice Type
Presolicitation
 
NAICS
541715 — Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
 
Contracting Office
FA8750 AFRL RIK ROME NY 13441-4514 USA
 
ZIP Code
13441-4514
 
Solicitation Number
FA875020S7007
 
Archive Date
09/30/2022
 
Point of Contact
Dr. Nathaniel Gemelli, Stratagem TPOC, Phone: 315-330-3252, Amber Buckley, Contracting Officer, Phone: 315-330-3605
 
E-Mail Address
nathaniel.gemelli@us.af.mil, amber.buckley@us.af.mil
(nathaniel.gemelli@us.af.mil, amber.buckley@us.af.mil)
 
Description
NAICS CODE: 541715 FEDERAL AGENCY NAME: Department of the Air Force, Air Force Materiel Command, AFRL - Rome Research Site, AFRL/Information Directorate, 26 Electronic Parkway, Rome, NY, 13441-4514 BAA ANNOUNCEMENT TYPE: Initial announcement BROAD AGENCY ANNOUNCEMENT (BAA) TITLE: Stratagem: Applying State-of-the-Art Artificial Intelligence and Machine Learning Approaches to Air Battle Management BAA NUMBER: FA8750-20-S-7007 PART I - OVERVIEW INFORMATION This announcement is for an Open, 2 Step BAA which is open and effective until 29 Sep 2023. Only white papers will be accepted as initial submissions; formal proposals will be accepted by invitation only. While white papers will be considered if received prior to 4 PM Eastern Standard Time (EST) on 31 Mar 2023, the following submission dates are suggested to best align with projected funding: For Focus Area 1 ONLY: FY20 by 13 Nov 2019 FY21 by 31 Mar 2020 FY22 by 31 Mar 2021 FY23 by 31 Mar 2022 For Focus Areas 2 and 3 ONLY: All potential Offerors are requested to wait to submit white papers for focus areas 2 & 3 until the BAA announcement is updated with specific dates. Due to funding limitations, it is anticipated that only one award will be made under Focus Area 2 and one award under Focus Area 3. Therefore, when the BAA announcement is updated to include white paper dates, if requested, proposals will also have a specific due date. In lieu of an Industry Day, the Government will accept questions regarding the synopsis via email to the TPOCS identified in Section VII until 12:00 PM EST on 30 OCT 2019. The Government will then amend the synopsis with a Q&A document. After its initial posting, the Q&A document will not be updated. Any future changes to the BAA will be done via amendment to the synopsis. Offerors should monitor the Federal Business Opportunities website at http://www.fbo.gov in the event this announcement is amended. CONCISE SUMMARY OF TECHNOLOGY REQUIREMENT: AFRL/RI is seeking innovative research to create a capability to develop new Artificial Intelligence-based capabilities that can reason in real-time about developments in the battlespace during wartime engagements and assist planners and decision makers responsible for reacting to those developments. As the Air Force begins to operate in contested environments against near-peer and/or peer adversaries, the demands on operational planners and warfighters will quickly increase, thereby requiring decision support assistance. In recent years, major developments in the field of Artificial Intelligence (AI) for video game playing agents has suggested that some of these approaches could be considered as candidates to provide that form of decision support. The objective of this effort is three-fold. First, AFRL is looking to investigate and develop machine intelligence approaches for supporting and performing operations in complex adversarial environments. It is imperative to explore the use of existing decision support AI algorithms and machine learning methods applicable to developing strategies and playing complex games. Second, AFRL desires the capability to capture human expertise to augment warfighter capability through the use of game play in Air Force (AF) relevant ""video games"" via interactive components. We will record and learn from subject matter experts and end-user warfighters using these AF video games that are motivated by operational use cases. Finally, AFRL will apply forms of domain adaptation techniques to transfer AI strategies and/or machine learned models from video game play to AF relevant challenge problems/simulations. AFRL envisions developing AI approaches in unclassified game playing domains and attempting to perform transfer to either unclassified or classified scenarios in tools like Advanced Framework for Simulation Integration and Modeling (AFSIM) or others. In order to develop these capabilities, focus will be placed on using existing game playing engines and newly developed interactive ""simulation"" environments that can be played by operators, either supported by or against AI agents. BAA ESTIMATED FUNDING: Total funding for this BAA is approximately $9.9M. Individual awards will not normally exceed 24 months with dollar amounts normally ranging from $300,000 to $2,000,000. There is also the potential to make awards up to any dollar value as long as the value does not exceed the available BAA ceiling amount. ANTICIPATED INDIVIDUAL AWARDS: Multiple Awards are anticipated. TYPE OF INSTRUMENTS THAT MAY BE AWARDED: Procurement contracts, grants, cooperative agreements or other transactions (OT) depending upon the nature of the work proposed. In the event that an Other Transaction for Prototype agreement is awarded as a result of this competitive BAA, and the prototype project is successfully completed, there is the potential for a prototype project to transition to award of a follow-on production contract or transaction. The Other Transaction for Prototype agreement itself will also contain a similar notice of a potential follow-on production contract or agreement. AGENCY CONTACT INFORMATION: All white paper submissions and any questions of a technical nature shall be directed to the cognizant Technical Point of Contact (TPOC) as specified below (unless otherwise specified in the technical area) (email requests are preferred): ��� Stratagem TPOC: ��� Dr. Nathaniel Gemelli ��� AFRL/RISC ��� 525 Brooks Rd ��� Rome, NY 13441-4505 ��� Telephone: (315)330-3252 ��� Email: nathaniel.gemelli@us.af.mil ��� Copies of white paper submissions should also be sent to: ��� Stratagem BAA MANAGER: ��� Mr. Warren Geiler ��� AFRL/RISC ��� 525 Brooks Rd ��� Rome, NY 13441-4505 ��� Telephone: (315)330-2122 ��� Email: warren.geiler.1@us.af.mil Questions of a contractual/business nature shall be directed to the cognizant contracting officer, as specified below (email requests are preferred): ��� Ms. Amber Buckley ��� Telephone (315) 330-3605 ��� Email: amber.buckley@us.af.mil Emails must reference the solicitation (BAA) number and title of the acquisition. Pre-Proposal Communication between Prospective Offerors and Government Representatives: Dialogue between prospective offerors and Government representatives is encouraged. Technical and contracting questions can be resolved in writing or through open discussions. Discussions with any of the points of contact shall not constitute a commitment by the Government to subsequently fund or award any proposed effort. Only Contracting Officers are legally authorized to commit the Government. Offerors are cautioned that evaluation ratings may be lowered and/or proposal rejected if proposal preparation (Proposal format, content, etc.) and/or submittal instructions are not followed. ������������������������������������������Amendment No. 1 to BAA FA8750-20-S-7007 The purpose of this amendment is to: Update the date the BAA is open until in Part I and Part II, Section IV.1 to 29 SEP 2023; Part II, Section I, TECHNOLOGY REQUIREMENTS, updates the language in Focus Area 1 as follows; � Focus Area 1 � Machine Intelligence for Strategy Development: The focus of this area is to explore the use of new and existing algorithms and learning methods applicable to developing strategies.� The Machine Intelligence for Strategy Development focus area seeks the development of a model architecture for an intelligent agent, determining which pieces that absolutely must be included in the design of an agent capable of reasoning in increasingly complex environments.� This model architecture should be based around two main technologies: Computational Game Theory and Machine Learning, and will address technical challenges 1, 2, 3, and 4. However, compelling technical approaches that include elements outside of Computational Game Theory and Machine Learning would also be of interest. The end goal is to develop a new state-of-the-art approach for matching and then exceeding expert human gameplay in advanced wargames.� In particular, Focus Area 1 (FA1) should produce blue/red agents that can assist and/or play against operational planners in real-time as well as run large batches of games to produce plan options for operators to evaluate against their desired operational objectives.� Plan quality will be a measure of number of objectives achieved operating within the constraints of currently available forces and forces arriving at different intervals during execution of a plan.� Plans should also consider the timing (schedule) of forces arriving to battle, sustainment of existing forces in battle (logistics of resupply), and possible unknown capabilities of the adversary.� Plans shall be saved at the conclusion of game play so they can be output in a to-be-determined format.� Games will be recorded and stored such that we can continually build a game replay dataset for training agents. In terms of size of operation and time, AFRL is considering wargames with an operational area of as little as 50 miles by 50 miles and as large as 500 miles by 500 miles.� Timeline of execution of up to 100 days with a �turn� of the game being 1 day of execution.� Referencing technical challenge 1, AFRL plans to model units at the squadron, brigade/battalion, and naval ship level of granularity. AFRL will be considering terrain, cities, and weather as modifiers to the offensive and defensive capabilities of a given unit, and conflict between adversary units will be reflected by simple probabilistic models, defined in the rules of the game.� For example, the level of fidelity might be, given two equally modified units of different sizes, the larger unit will take (probabilistically) less damage than the smaller unit.� At the end of a turn of conflict (1 day), each unit should have its capability updated � to include things such as number of troops/aircraft killed in action, wounded in action, how much munition is left, etc.� Additional modifiers to offensive and defensive capability (at least for ground) should include terrain differences (e.g. higher elevation increases capability and vice versa) or city cover as well as time �dug in� to a location (being in a location for longer probably reflects higher level of defensive capability).� Probability modifiers for air and naval conflict should be based on capabilities of the given craft and what they are in conflict with (i.e. air-to-air, air-to-ground, air-to-navel, etc).� All of these concepts should be described in the game representation. ��� 3.� Part I, Overview information and Part II, Section IV.1, extend the white paper due date for Focus Area 1 for FY20 from 13 NOV 2019 to 22 NOV 2019 as shown below; For Focus Area 1 ONLY: FY20 by� 22 Nov� 2019 FY21 by 31 Mar 2020 FY22 by 31 Mar 2021 FY23 by 31 Mar 2022 For Focus Areas 2 and 3 ONLY: All potential Offerors are requested to wait to submit white papers for focus areas 2 & 3 until the BAA announcement is updated with specific dates. Due to funding limitations, it is anticipated that only one award will be made under Focus Area 2 and one award under Focus Area 3. Therefore, when the BAA announcement is updated to include white paper dates, if requested, proposals will also have a specific due date. No other changes are made. ������������������������������������� Amendment No. 2 to BAA FA8750-20-S-7007 The purpose of this amendment is to: Upload the Q&A document referenced in Part I-Overview Information and update the language as shown below: In lieu of an Industry Day, the Government will accept questions regarding the synopsis via email to the TPOCS identified in Section VII until 12:00 PM EST on 30 OCT 2019. The Government will then amend the synopsis with a Q&A document. After its initial posting, the Q&A document will not be updated. Any future changes to the BAA will be done via amendment to the synopsis. See the Stratagem BAA Q&A document dated 8 NOV 2019 attached to this announcement. No other changes are made. PLEASE SEE BAA Q&A ATTACHMENT FOR AMENDMENT 2 ������������������������������������� Amendment No. 3 to BAA FA8750-20-S-7007 The purpose of this amendment is to update the Stratagem TPOC as shown below. In Part I and Part II Section VII, the Stratagem TPOC is changed as follows: From: Stratagem TPOC: ��� Dr. Nathaniel Gemelli ��� AFRL/RISC ��� 525 Brooks Rd ��� Rome, NY 13441-4505 ��� Telephone: (315)330-3252 ��� Email:� nathaniel.gemelli@us.af.mil To: Stratagem TPOC: ��� Brayden Hollis ��� AFRL/RISC ��� 525 Brooks Rd ��� Rome, NY 13441-4505 ��� Telephone: (315)330-2331 ��� Email:� brayden.hollis.1@us.af.mil � No other changes are made. � ������������� AMENDMENT 4 TO BAA FA8750-20-S-7007 The purpose of this modification is to republish the original announcement, incorporating any previous amendments, pursuant to FAR 35.016(c). This republishing also includes the following changes: Part I, Overview Information: Updates FBO reference to Beta SAM website;� � Part II, Full Text Announcement: Section III.2.b.2, updates the DCSA website; Section IV.3.a, updates the DCSA website; Section IV.4.b and IV.4.c. updates clause dates; Section IV.4.e, updated the link to reference the Beta SAM website; Section VI.1, updates the RI Specific Proposal Preparation Instructions Beta SAM link; Section VI.7, updates the applicable provisions; Section VII, updates the AFFARS Ombudsman clause date No other changes have been made. SEE ATTACHMENT FOR FULL ANNOUNCEMENT DETAILS. � �
 
Web Link
SAM.gov Permalink
(https://beta.sam.gov/opp/8f5b5566ae9342faab3b8235a4347768/view)
 
Record
SN05836889-F 20201025/201023230146 (samdaily.us)
 
Source
SAM.gov Link to This Notice
(may not be valid after Archive Date)

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