| Funding Opportunity ID: |
313085 |
| Opportunity Number: |
HR001119S0030 |
| Opportunity Title: |
Competency-Aware Machine Learning (CAML) |
| Opportunity Category: |
Discretionary |
| Opportunity Category Explanation: |
|
| Funding Instrument Type: |
Cooperative Agreement
Other
Procurement Contract |
| Category of Funding Activity: |
Science and Technology and other Research and Development |
| Category Explanation: |
|
| CFDA Number(s): |
12.910 |
| Eligible Applicants: |
Others (see text field entitled “Additional Information on Eligibility” for clarification) |
| Additional Information on Eligibility: |
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. |
| Agency Code: |
DOD-DARPA-DSO |
| Agency Name: |
Department of Defense
DARPA – Defense Sciences Office |
| Posted Date: |
Feb 19, 2019 |
| Close Date: |
Apr 22, 2019 See Full Announcement for details. |
| Last Updated Date: |
Feb 19, 2019 |
| Award Ceiling: |
$0 |
| Award Floor: |
$0 |
| Estimated Total Program Funding: |
|
| Expected Number of Awards: |
|
| Description: |
The Defense Sciences Office (DSO) at the Defense Advanced Research Projects Agency (DARPA) is soliciting innovative research proposals in the area of competency-awareness machine learning, whereby an autonomous system can self-assess its task competency and strategy and express both in a human-understandable form. This competency-awareness capability contributes to the goal of transforming autonomous systems from tools into trusted, collaborative partners. The resulting competency-aware machine learning systems will enable machines to control their behaviors to match user expectations and allow human operators to quickly and accurately gain insight into a system’s competence in complex, time-critical, dynamic environments. The Competency-Aware Machine Learning (CAML) program will, in this way, improve the efficiency and effectiveness of human-machine teaming. Proposed research should investigate innovative approaches that enable revolutionary advances in science. DSO will exclude proposals that propose evolutionary improvement to the existing state of practice. |
| Version: |
1 |
