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IIS: Robust Intelligence  (RI)

Name Email Phone Room
James  J. Donlon (703) 292-8074   
Rebecca  Hwa (703) 292-7148   
Tatiana  D. Korelsky (703) 292-8930   
David  Miller (703) 292-8930   
Erion  Plaku (703) 292-8695   
Kenneth  C. Whang (703) 292-5149   
Jie  Yang (703) 292-4768   


Robust intelligence encompasses foundational computational research needed to understand and develop systems that can sense, learn, reason, communicate, and act in the world; exhibit flexibility, resourcefulness, creativity, real-time responsiveness and long-term reflection; use a variety of representation or reasoning approaches; and demonstrate competence in complex environments and social contexts. The RI program accepts research proposals aimed at contributing deeper understanding and new insights in and across the disciplinary areas outlined below. Proposals focused on application and fielding of established methods should be directed to programs focused on the respective application areas. Areas within RI include:

  • Artificial intelligence (AI): All matters of learning, abstraction and inference required for intelligent behavior, and including architectures for intelligence, integrated intelligent agents, and multi-agent systems. Aspects of intelligence include knowledge representation, logical and probabilistic reasoning, planning, search, constraint satisfaction, and optimization.
  • Machine learning: The study of algorithms and models that are able to solve tasks by generalizing from data. 
  • Computer vision: The ability of systems to sense and reason about the visual world. Research in this area ranges from novel work in computational imaging to methods for high-level semantic understanding of images or videos.
  • Human language technologies: The ability of intelligent systems to analyze, produce, translate, and respond to human text and speech.
  • Robotics: The design, construction, operation, and use of machines capable of carrying out a complex series of actions automatically. Robotics proposals submitted to RI must advance knowledge and understanding specifically in the embodiment of intelligent systems.
  • Computational Neuroscience: Theory and analysis of computational processes in the nervous system, including approaches to the above RI problem areas that are grounded in neural computation and neuroscience.