1. Introductory Remarks Robust Intelligence Solicitation Edwina Rissland Daniel DeMenthon, George Lee, Tanya Korelsky, Ken Whang (The Robust Intelligence Cluster)

2. 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.

3. Current IIS Solicitation: NSF 06-572 (replacing NSF 05-551 & NSF 04-528) 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)

4. 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/  http://www.nsf.gov/cise/iis/about.jsp

5. 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.

6. 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.

7. 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)

8. 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