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Assured Neuro Symbolic Learning and Reasoning (ANSR)

ID: HR001122S0039 • Type: Posted

Description

The overarching goal of the ANSR program is to advance hybrid AI algorithms, and develop evidence-based techniques that support confident assurance judgments for these algorithms. The program intends to explore diverse hybrid architectures that can be seeded with prior knowledge, acquire both statistical and symbolic knowledge through learning, and adapt learned representations. The program intends to demonstrate and evaluate hybrid AI techniques through DoD mission relevant use-cases where assurance and autonomy are mission critical.
Background
The Defense Advanced Research Projects Agency (DARPA) is soliciting innovative proposals for the Assured Neuro Symbolic Learning and Reasoning (ANSR) program. The program aims to advance hybrid AI algorithms and develop evidence-based techniques that support confident assurance judgments for these algorithms. It intends to explore diverse hybrid architectures that can be seeded with prior knowledge, acquire both statistical and symbolic knowledge through learning, and adapt learned representations. The program seeks breakthrough innovations in the form of new hybrid AI algorithms that deeply integrate symbolic reasoning with data-driven learning to create robust, assured, and therefore trustworthy systems.

Grant Details
The program envisions a new take on representation learning and inference to lead towards hybrid AI. It seeks to modify both the training and inference procedures to interleave symbolic and neural representations for iterative inference and mutual adaptation of the representations to exploit the benefits and reduce the limitations of each representation. The development in the program will be orchestrated in four technical areas (TAs) summarized below: TA1: Algorithms and Architectures, TA2: Specification and Assurance, TA3: Platforms and Capability Demonstration, TA4: Assurance Assays and Evaluation.

Eligibility Requirements
Eligible applicants include organizations capable of developing innovative proposals in the areas of interest such as Artificial Intelligence (AI) algorithms and architectures that deeply integrate symbolic reasoning with data-driven machine learning. The program anticipates multiple awards in technical area (TA) 1. No more than two awards in each of TA2 and TA3, and one award in TA4.

Period of Performance
The period of performance for the grant includes various dates such as Abstract Due Date, Questions Due Date, Proposal Due Date, as well as anticipated phases for technology development, simulation-based experiments, live exercises at DoD facilities, and after-action reviews.

Grant Value
The total value of the grant is not explicitly provided in the document.

Overview

Category of Funding
Science and Technology and other Research and Development
Funding Instruments
Cooperative Agreement
Other
Procurement Contract
Grant Category
Discretionary
Cost Sharing / Matching Requirement
False
Source
On 6/1/22 Defense Advanced Research Projects Agency posted grant opportunity HR001122S0039 for Assured Neuro Symbolic Learning and Reasoning (ANSR). The grant will be issued under grant program 12.910 Research and Technology Development.

Timing

Posted Date
June 1, 2022, 12:00 a.m. EDT
Closing Date
Nov. 28, 2022, 12:00 a.m. EST Past Due
Closing Date Explanation
See Full Announcement for details.
Last Updated
June 3, 2022, 4:12 p.m. EDT
Version
2
Archive Date
Dec. 28, 2022

Eligibility

Eligible Applicants
Others (see text field entitled "Additional Information on Eligibility" for clarification)
Additional Info
All responsible sources capable of satisfying the Government's needs may submit a proposal that shall be considered by DARPA. See the Eligibility Information section of the BAA for more information.

Contacts

Contact
DARPA - Information Innovation Office
Email Description
None
Contact Phone
(703) 696-2258
Additional Information
SAM.gov Contract Opportunities

Documents

Posted documents for HR001122S0039

Grant Awards

Grants awarded through HR001122S0039

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