An ensemble learning and problem solving architecture for airspace management

Xiaoqin Zhang, Sungwook Yoon, Phillip DiBona, Darren Scott Appling, Li Ding, Janardhan Rao Doppa, Derek Green, Jinhong K. Guo, Ugur Kuter, Geoff Levine, Reid L. MacTavish, Daniel McFarlane, James R. Michaelis, Hala Mostafa, Santiago Ontañón, Charles Parker, Jainarayan Radhakrishnan, Anton Rebguns, Bhavesh Shrestha, Zhexuan SongEthan B. Trewhitt, Huzaifa Zafar, Chongjie Zhang, Daniel Corkill, Gerald DeJong, Thomas G. Dietterich, Subbarao Kambhampati, Victor Lesser, Deborah L. McGuinness, Ashwin Ram, Diana Spears, Prasad Tadepalli, Elizabeth T. Whitaker, Weng Keen Wong, James A. Hendler, Martin O. Hofmann, Kenneth Whitebread

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper we describe the application of a novel learning and problem solving architecture to the domain of airspace management, where multiple requests for the use of airspace need to be reconciled and managed automatically. The key feature of our "Generalized Integrated Learning Architecture" (GILA) is a set of integrated learning and reasoning (ILR) systems coordinated by a central meta-reasoning executive (MRE). Each ILR learns independently from the same training example and contributes to problem-solving in concert with other ILRs as directed by the MRE. Formal evaluations show that our system performs as well as or better than humans after learning from the same training data. Further, GILA outperforms any individual ILR run in isolation, thus demonstrating the power of the ensemble architecture for learning and problem solving.

Original languageEnglish (US)
Title of host publicationProceedings of the 21st Innovative Applications of Artificial Intelligence Conference, IAAI-09
Pages203-210
Number of pages8
StatePublished - Dec 1 2009
Event21st Innovative Applications of Artificial Intelligence Conference, IAAI-09 - Pasadena, CA, United States
Duration: Jul 14 2009Jul 16 2009

Publication series

NameProceedings of the 21st Innovative Applications of Artificial Intelligence Conference, IAAI-09

Other

Other21st Innovative Applications of Artificial Intelligence Conference, IAAI-09
CountryUnited States
CityPasadena, CA
Period7/14/097/16/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Zhang, X., Yoon, S., DiBona, P., Appling, D. S., Ding, L., Doppa, J. R., Green, D., Guo, J. K., Kuter, U., Levine, G., MacTavish, R. L., McFarlane, D., Michaelis, J. R., Mostafa, H., Ontañón, S., Parker, C., Radhakrishnan, J., Rebguns, A., Shrestha, B., ... Whitebread, K. (2009). An ensemble learning and problem solving architecture for airspace management. In Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference, IAAI-09 (pp. 203-210). (Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference, IAAI-09).