Abstract collage of science-related imagery

Important Information for Proposers

Any proposal submitted in response to this funding opportunity should be submitted in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. The NSF PAPPG is regularly revised and it is the responsibility of the proposer to ensure that the proposal meets the requirements specified in this solicitation and the applicable version of the PAPPG. Submitting a proposal prior to a specified deadline does not negate this requirement.

Supports computational research in artificial intelligence, machine learning, computer vision, human language technologies and computational neuroscience.

Synopsis

Robust Intelligence (RI) encompasses foundational computational research needed to understand and develop systems that can sense, learn, reason, communicate, and act in the world; exhibit flexibility, resourcefulness, creativity, real-time responsiveness and long-term reflection; use a variety of representation or reasoning approaches; and demonstrate competence in complex environments and social contexts. The RI program accepts research proposals aimed at contributing deeper understanding and new insights in and across the disciplinary areas outlined below. Areas within RI include:

  • Artificial intelligence (AI): All matters of learning, abstraction and inference required for intelligent behavior, and including architectures for intelligence, integrated intelligent agents, and multi-agent systems. Aspects of intelligence include knowledge representation, logical and probabilistic reasoning, planning, search, constraint satisfaction, and optimization.
  • Machine learning: The study of algorithms and models that are able to solve tasks by generalizing from data. 
  • Computer vision: The ability of systems to sense and reason about the visual world. Research in this area ranges from novel work in computational imaging to methods for high-level semantic understanding of images or videos.
  • Human language technologies: The ability of intelligent systems to analyze, produce, translate, and respond to human text and speech.
  • Computational neuroscience: Theory and analysis of computational processes in the nervous system, including approaches to the above RI problem areas that are grounded in neural computation and neuroscience.

Note that projects that simply apply existing RI techniques to particular domains of science and engineering are more appropriate for funding opportunities issued by the NSF programs cognizant for those domains. Investigators wishing to submit proposals in robotics, including robotics research in the design, construction, operation, and use of machines capable of carrying out a complex series of actions automatically, should submit proposals to the Foundational Research in Robotics (Robotics) program.

Program contacts

James J. Donlon
jdonlon@nsf.gov (703) 292-8074 CISE/IIS
Rebecca Hwa
rhwa@nsf.gov (703) 292-7148 CISE/IIS
Tatiana D. Korelsky
tkorelsk@nsf.gov (703) 292-8930 CISE/IIS
Roger Mailler
rmailler@nsf.gov (703) 292-7982 CISE/IIS
Juan P. Wachs
jwachs@nsf.gov (703) 292-8714 CISE/IIS
Erion Plaku
eplaku@nsf.gov (703) 292-8695
Kenneth C. Whang
kwhang@nsf.gov (703) 292-5149 CISE/IIS
Jie Yang
jyang@nsf.gov (703) 292-4768 CISE/IIS