Planning and learning in permutation groups

Amos Fiat*, Shahar Moses, Adi Shamir, Ilan Shimshoni, Gabor Tardos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Planning is defined as the problem of synthesizing a desired behavior from given basic operations, and learning is defined as the dual problem of analyzing a given behavior to determine the unknown basic operations. Algorithms for solving these problems in the context of invertible operations on finite-state environments are developed. In addition to their obvious artificial intelligence applications, the algorithms can efficiently find the shortest way to solve Rubik's cube, test ping-pong protocols, and solve systems of equations over permutation groups.

Original languageEnglish
Title of host publicationAnnual Symposium on Foundations of Computer Science (Proceedings)
PublisherPubl by IEEE
Pages274-279
Number of pages6
ISBN (Print)0818619821, 9780818619823
DOIs
StatePublished - 1989
Event30th Annual Symposium on Foundations of Computer Science - Research Triangle Park, NC, USA
Duration: 30 Oct 19891 Nov 1989

Publication series

NameAnnual Symposium on Foundations of Computer Science (Proceedings)
ISSN (Print)0272-5428

Conference

Conference30th Annual Symposium on Foundations of Computer Science
CityResearch Triangle Park, NC, USA
Period30/10/891/11/89

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