Learning generalized plans using abstract counting

Siddharth Srivastava, Neil Immerman, Shlomo Zilberstein

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

18 Citations (Scopus)

Abstract

Given the complexity of planning, it is often beneficial to create plans that work for a wide class of problems. This facilitates reuse of existing plans for different instances drawn from the same problem or from an infinite family of similar problems. We define a class of such planning problems called generalized planning problems and present a novel approach for transforming classical plans into generalized plans. These algorithm-like plans include loops and work for problem instances having varying numbers of objects that must be manipulated to reach the goal. Our approach takes as input a classical plan for a certain problem instance. It outputs a generalized plan along with a classification of the problem instances where it is guaranteed to work. We illustrate the utility of our approach through results of a working implementation on various practical examples.

Original languageEnglish (US)
Title of host publicationAAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference
Pages991-997
Number of pages7
Volume2
StatePublished - Dec 24 2008
Externally publishedYes
Event23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08 - Chicago, IL, United States
Duration: Jul 13 2008Jul 17 2008

Other

Other23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08
CountryUnited States
CityChicago, IL
Period7/13/087/17/08

Fingerprint

Planning

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Srivastava, S., Immerman, N., & Zilberstein, S. (2008). Learning generalized plans using abstract counting. In AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference (Vol. 2, pp. 991-997)

Learning generalized plans using abstract counting. / Srivastava, Siddharth; Immerman, Neil; Zilberstein, Shlomo.

AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference. Vol. 2 2008. p. 991-997.

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

Srivastava, S, Immerman, N & Zilberstein, S 2008, Learning generalized plans using abstract counting. in AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference. vol. 2, pp. 991-997, 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08, Chicago, IL, United States, 7/13/08.
Srivastava S, Immerman N, Zilberstein S. Learning generalized plans using abstract counting. In AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference. Vol. 2. 2008. p. 991-997
Srivastava, Siddharth ; Immerman, Neil ; Zilberstein, Shlomo. / Learning generalized plans using abstract counting. AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference. Vol. 2 2008. pp. 991-997
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