Division of Information & Intelligent Systems
Artificial Intelligence and Cognitive Science
This program has been archived.
Important Notice to Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG), NSF 13-1, was issued on October 4, 2012 and is effective for proposals submitted, or due, on or after January 14, 2013. Please be advised that, depending on the specified due date, the guidelines contained in NSF 13-1 may apply to proposals submitted in response to this funding opportunity.
Please be aware that significant changes have been made to the PAPPG to implement revised merit review criteria based on the National Science Board (NSB) report, National Science Foundation's Merit Review Criteria: Review and Revisions. While the two merit review criteria remain unchanged (Intellectual Merit and Broader Impacts), guidance has been provided to clarify and improve the function of the criteria. Changes will affect the project summary and project description sections of proposals. Annual and final reports also will be affected.
A by-chapter summary of this and other significant changes is provided at the beginning of both the Grant Proposal Guide and the Award & Administration Guide.
The Artificial Intelligence and Cognitive Science (AICS) program focuses on advancing the state of the art in Artificial Intelligence and Cognitive Science. The program supports research and related education activities fundamental to the development of computer systems capable of performing a broad variety of intelligent tasks, and to the development of computational models of intelligent behavior across the spectrum of human intelligence.
Examples of performance-oriented topics include intelligent agents, planning, automated reasoning, machine learning, case-based reasoning, knowledge representation methodologies, and architectures for combining intelligent tasks such as perception, reasoning, planning, learning, and action. Examples of cognitive-oriented topics include analogical reasoning, concept formation and evolution, argumentation, integration of knowledge from diverse sources and experience, knowledge acquisition by human learners, manipulation and development of taxonomies and classification systems, collaborative behavior, and adaptation and learning.
Many topics, such as the support of human decision making and diagnosis in complex task domains, require a combination of the two orientations.
Digital Society and Technologies
Human Language and Communication
Information and Data Management
Science and Engineering Information Integration and Informatics
THIS PROGRAM IS PART OF
Data, Inference and Understanding Cluster
What Has Been Funded (Recent Awards Made Through This Program, with Abstracts)
Map of Recent Awards Made Through This Program