Login not required to view content
DARPA funds unique and innovative research through the private sector, academic and other non-profit organizations as well as government labs.
DARPA research runs the gamut from conducting scientific investigations in a laboratory, to building full-scale prototypes of military systems. We fund research in biology, medicine, computer science, chemistry, physics, engineering, mathematics, material sciences, social sciences, neuroscience, and more.
|Cloud-Oriented Social Media Inference And Counteraction (COSMIC)|
Principal Investigator: Jim Hendler
Co Investigator: Deborah L. McGuinness
Description: COSMIC will combine novel algorithms from sentiment analysis, probabilistic temporal learning of diffusion of messages/opinion in social networks, forecasting and prediction of the reach of messages in social media, and game-theoretic methods to counteract diffusion of messages, into a highly modular, loosely-coupled framework and software platform to address the objectives of DARPA’s Social Media in Strategic Communication (SMISC) Program.
|Cognitive Assistant that Learns and Organizes (CALO)|
Principal Investigator: Deborah L. McGuinness
Description: The goal of the project CALO, for Cognitive Assistant that Learns and Organizes, is to create cognitive software systems, that is, systems that can reason, learn from experience, be told what to do, explain what they are doing, reflect on their experience, and respond robustly to surprise. Rensselaer is leading the explanation efforts.
|Generalized Integrated Learning Architecture (GILA)|
Principal Investigator: Jim Hendler and Deborah L. McGuinness
Description: The Generalized Integrated Learning Architecture [GILA] is a general-purpose integrated multi-agent platform that solves domain problems by learning from a problem-solution pair submitted by a human expert. One of the key purposes of GILA is to learn how humans solve complex problems and apply this knowledge to future problems. A complex problem domain known as the Airspace Control Scenario has been chosen to drive the development of GILA and evaluate its performance. The objective of this problem domain is to resolve conflicts in a collection of airspace allocations for aircrafts.