Introductory Remarks Robust Intelligence Solicitation

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Introductory RemarksRobust Intelligence
Solicitation

• Edwina Rissland
• Daniel DeMenthon, George Lee, Tanya Korelsky,
  Ken Whang
• (The Robust Intelligence Cluster)

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Information and Intelligent Systems Division (IIS)

• Robust Intelligence (RI)
• Computer vision
• Robotics
• Artificial intelligence cognitive science
• Human language communication
• Computational neuroscience.
• Human-Centered Computing (HCC)
• 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.

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Current IIS Solicitation NSF 06-572 (replacing
NSF 05-551 NSF 04-528)

• Three Core Technical Areas
• Robust Intelligence (RI)
• Human-Centered Computing (HCC)
• Information Integration Informatics (III)
• Two Cross-Cutting Technical Areas
• Human-Robot (and/or Agents) Interaction (HRI)
• Information Privacy and Security (IPS)
• Curriculum Development (IISCD)

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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

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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.

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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.

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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)

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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