1. Introductory RemarksRobust 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) • 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/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