Download Insights on AI Funding at the National Science Foundation

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

A New Kind of Science wikipedia , lookup

Signals intelligence wikipedia , lookup

Natural computing wikipedia , lookup

Artificial intelligence wikipedia , lookup

Theoretical computer science wikipedia , lookup

Computational linguistics wikipedia , lookup

Transcript
Introductory Remarks
Robust Intelligence Solicitation
Edwina Rissland
Daniel DeMenthon, George Lee,
Tanya Korelsky, Ken Whang
(The Robust Intelligence Cluster)
Information and Intelligent Systems
Division (IIS)

Robust Intelligence (RI)






Human-Centered Computing (HCC)


Computer vision
Robotics
Artificial intelligence & cognitive science
Human language & communication
Computational neuroscience.
Digital society & technologies; Human computer interaction; and
Universal access.
Information Integration & Informatics (III)

Digital government; Digital libraries & archives; Information, data,
and knowledge management; and Science & Engineering
information integration and informatics.
Current IIS Solicitation: NSF 06-572
(replacing NSF 05-551 & NSF 04-528)

Three Core Technical Areas:




Two Cross-Cutting Technical Areas:



Robust Intelligence (RI)
Human-Centered Computing (HCC)
Information Integration & Informatics (III)
Human-Robot (and/or Agents) Interaction (HRI)
Information Privacy and Security (IPS)
Curriculum Development (IISCD)
NSF 06-572 Solicitation

Three classes of proposal:






Large projects
 $900K - $1.8M (5-8 PIs.)
Medium projects
 $450K - $900K (2-4 PIs.)
Small projects
 up to $450K (Single PI)
Deadlines:

October 19, 2006 for Large projects

November 02, 2006 for Medium projects

December 06, 2006 for Small projects
http://www.nsf.gov/, search for IIS
http://www.nsf.gov/cise/iis/about.jsp
What is Robust Intelligence?

“…Robust Intelligence (RI) encompasses
computational understanding and modeling of the
many human and animal capabilities that
demonstrate intelligence and adaptability in
unstructured and uncertain environments…”

Synergistic collaboration and integration of some of
the basic elements in AICS, CV, ROB, HCL, and
CNS to achieve intelligence and flexibility in reaction
to dynamic changing environments.

Better performance in unstructured environments.
Systems that can learn from experience.

RI Topics - Examples

Problem solving architectures that integrate reasoning, motor,
perceptual, and language capabilities and that can learn from
experience.

Hybrid architectures that integrate or combine different methods.

Computational models of human cognition, perception, and
communication.

Novel approaches to long-standing problems in computer vision,
language, learning, …

Vision systems that capture biological components and
capabilities.
RI Topics - Examples

Synergistic and collaborative research of innovative and
emerging technologies to improve the intelligence, mobility,
autonomy, manipulability, adaptability, and interactivity of
robotic systems operating in unstructured and uncertain
environments

Research on intelligent and assistive robotics, neuro-robotics,
multi-robot coordination and cooperation, and micro- and
nano-robotics

Computational approaches and architectures for analyzing,
understanding, generating and summarizing speech, text and
other communicative forms (e.g., gesture, haptic)
RI Topics - Examples





Computational models of meaning, intent, and realization at
various levels of language representation
Novel approaches to longstanding language processing problems
such as speaker and language recognition, machine translation,
evaluation metrics, multilingual man-machine communication
Computational approaches to language processing for minority
language groups, aging, disabled, etc.
Functional modeling, theory, and analysis of the computational,
representational, and coding strategies of neural systems.
Neurally grounded computational approaches to computer vision,
robotics, communication, and reasoning