The Duke Funding Alert newsletter, published every Monday, provides information on all new and updated grants and fellowships added to the database during the prior week. This listserv is restricted to members of the Duke community.
Lifelong Learning Machines (L2M)
DARPA is soliciting highly innovative research proposals for the development of fundamentally new machine learning approaches that enable systems to learn continually as they operate and apply previous knowledge to novel situations. Current artificial intelligence (AI) systems only compute with what they have been programmed or trained for in advance; they have no ability to learn from data input during execution time, and cannot adapt on-line to changes they encounter in real environments. The goal of the Lifelong Learning Machines (L2M) program is to develop substantially more capable systems that are continually improving and updating from experience. Proposed research should investigate innovative approaches that support key lifelong learning machines technologies and enable revolutionary advances in the science of adaptive and intelligent systems. Specifically excluded is research that results in incremental improvements to the existing state of practice.
o Abstract Due Date: May 3, 2017
o Proposal Due Date: June 21, 2017
Areas of Interest
- Lifelong Learning Machine Systems (Technical Area 1)
- Physical Principles of Machine Learning from Nature (Technical Area 2)