Defense Advanced Research Projects AgencyTagged Content List

Artificial Intelligence and Human-Computer Symbiosis Technologies

Technology to facilitate more intuitive interactions between humans and machines

Showing 46 results for Artificial Intelligence + Algorithms RSS
March 5, 2019,
Executive Conference Center
The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is sponsoring a Proposers Day to provide information to potential proposers on the objectives of an anticipated Broad Agency Announcement (BAA) for the Science of Artificial Intelligence and Learning for Open-world Novelty (SAIL-ON) program.
May 13, 2016,
Executive Conference Center
The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is sponsoring a Proposers Day to provide information to potential proposers on the objectives of an anticipated Broad Agency Announcement (BAA) for the TRAnsformative DESign (TRADES) program. The Proposers Day will be held on Friday, May 13, 2016 from 8:30 AM to 12:30 PM (EDT) at the Executive Conference Center (4075 Wilson Blvd. Suite 350 Arlington, VA 22203).
August 29, 2017,
Webcast
The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is sponsoring a Proposers Day webcast to provide information to potential proposers on the objectives of an anticipated Research Announcement (RA) for the Young Faculty Award (YFA) program.
The ACE program seeks to increase trust in combat autonomy by using human-machine collaborative dogfighting as its challenge problem. This also serves as an entry point into complex human-machine collaboration. ACE will apply existing artificial intelligence technologies to the dogfight problem in experiments of increasing realism. In parallel, ACE will implement methods to measure, calibrate, increase, and predict human trust in combat autonomy performance.
The Artificial Intelligence Research Associate (AIRA) program is part of a broad DARPA initiative to develop and apply “Third Wave” AI technologies that are robust to sparse data and adversarial spoofing, and that incorporate domain-relevant knowledge through generative contextual and explanatory models.