This grant program aims to advance robust autonomy and automation in dynamic, unconstrained environments through novel learning capabilities. It focuses on enhancing existing Active Learning and Transfer Learning research by combining them to address their current deficiencies. The program seeks to fundamentally extend active learning to incorporate rich subject matter expert (SME) knowledge into the knowledge transfer process. Specifically, this grant is for enabling the robust transfer of knowledge from existing sources and facilitating the injection of new knowledge in situ. It will explore machine-initiated and human-guided exploration, machine reasoning for SME queries, and direct SME injection of domain knowledge, creating a more powerful and adaptable learning system.
Opportunity ID: 53951
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | ONRBAA10-017 |
| Funding Opportunity Title: | Active Transfer Learning (ATL) |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | CategoryExplanation |
| Funding Instrument Type: | Cooperative Agreement Grant Other Procurement Contract |
| Category of Funding Activity: | Science and Technology and other Research and Development |
| Category Explanation: | – |
| Expected Number of Awards: | – |
| Assistance Listings: | 12.300 — Basic and Applied Scientific Research |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 1 |
| Posted Date: | Apr 22, 2010 |
| Last Updated Date: | – |
| Original Closing Date for Applications: | Sep 04, 2010 White Papers are due 06/28/2010 at 2:00 PM Local Eastern Time. Full proposals are due 9/4/2010 at 2:00 PM Local Eastern Time. |
| Current Closing Date for Applications: | Sep 04, 2010 White Papers are due 06/28/2010 at 2:00 PM Local Eastern Time. Full proposals are due 9/4/2010 at 2:00 PM Local Eastern Time. |
| Archive Date: | Oct 04, 2010 |
| Estimated Total Program Funding: | – |
| Award Ceiling: | – |
| Award Floor: | – |
Eligibility
| Eligible Applicants: | Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled “Additional Information on Eligibility” |
| Additional Information on Eligibility: | All responsible sources from academia and industry may submit proposals under this BAA. Historically Black Colleges and Universities (HBCUs) and Minority Institutions (MIs) are encouraged to submit proposals and join others in submitting proposals. However, no portion of this BAA will be set aside for HBCU and MI participation. Federally Funded research & Development Centers (FFRDCs), including Department of Energy |
Additional Information
| Agency Name: | Office of Naval Research |
| Description: | The overall objective of this program is to conduct basic research that will help enable robust autonomy and automation in dynamic, unconstrained environments and contexts. The two science problems of interest are how a learning machine may leverage all relevant prior knowledge and how it may leverage occasional in situ availability of a subject matter expert (SME). This leads naturally to the existing research of Transfer Learning and Active Learning. The intent of this Program is to improve upon these two existing areas of research and combine them to produce a novel, powerful learning capability. The primary deficiency of active learning is that it typically involves only labeling exemplars and does not allow the SME to fully impart his/her rich domain knowledge as they would to a human student. A deficiency of transfer learning is that when it fails it is typically not possible for an SME to repair or complete the transfer in situ. By exploiting both of these deficiencies, this Program seeks to fundamentally extend the scope of active learning and incorporate it into the knowledge transfer process. The two specific technical goals are to capitalize on the occasional availability of an SME to enable 1) the robust transfer of knowledge from existing sources and 2) the injection of new knowledge in situ. This first technical goal includes both machine-initiated and human-guided exploration of existing knowledge sources as well as machine-based reasoning on knowledge sufficiency for prompting SME queries. This second technical goal includes both machine-initiated queries of target knowledge as well as SME injection of new, rich domain knowledge into the target. |
| Link to Additional Information: | Link to All ONR BAA’s |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
Jennifer Brown
Contract Specialist Phone 703-588-2432 Email:jennifer.brown4@navy.mil |
Version History
| Version | Modification Description | Updated Date |
|---|---|---|
Related Documents
Folder 53951 Full Announcement-1 -> new proposal checklist.pdf
Folder 53951 Full Announcement-1 -> onrbaa 10-017.pdf
Folder 53951 Other Supporting Documents-Admendment 0001 1 -> onrbaa 10-017 amendment 0001.pdf
Packages
| Agency Contact Information: | Jennifer Brown Contract Specialist Phone 703-588-2432 Email: jennifer.brown4@navy.mil |
| Who Can Apply: | Organization Applicants |
| Assistance Listing Number | Competition ID | Competition Title | Opportunity Package ID | Opening Date | Closing Date | Actions |
|---|---|---|---|---|---|---|
| 12.300 | ONRBAA10-017 | ACTIVE TRANSFER LEARNING (ATL) | PKG00018220 | Sep 04, 2010 | View |
Package 1
Mandatory forms
53951 RR_SF424_1_2-1.2.pdf
Optional forms
53951 PerformanceSite_1_4-1.4.pdf
53951 RR_OtherProjectInfo_1_3-1.3.pdf
53951 RR_Budget-1.1.pdf
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