Abstract collage of science-related imagery

Artificial Intelligence and Cognitive Science (AICS)

Status: Archived

Archived funding opportunity

This document has been archived.

Important information about NSF’s implementation of the revised 2 CFR

NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

Synopsis

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.

Program contacts

Edwina L. Rissland
Program Director
erisslan@nsf.gov (703) 292-8930

Awards made through this program

Browse projects funded by this program
Map of recent awards made through this program