Formalizing dependency directed backtracking and explanation based learning in refinement search

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

3 Scopus citations

Abstract

The ideas of dependency directed backtracking (DDB) and explanation based learning (EBL) have developed independently in constraint satisfaction, planning and problem solving communities. In this paper, I formalize and unify these ideas under the task-independent framework of refinement search, which can model the search strategies used in both planning and constraint satisfaction. I show that both DDB and EBL depend upon the common theory of explaining search failures, and regressing them to higher levels of the search tree. The relevant issues of importance include (a) how the failures are explained and (b) how many failure explanations are remembered. This task-independent understanding of DDB and EBL helps support cross-fertilization of ideas among Constraint Satisfaction, Planning and Explanation-Based Learning communities.

Original languageEnglish (US)
Title of host publicationProceedings of the National Conference on Artificial Intelligence
Editors Anon
Place of PublicationMenlo Park, CA, United States
PublisherAAAI
Pages757-762
Number of pages6
Volume1
StatePublished - 1996
EventProceedings of the 1996 13th National Conference on Artificial Intelligence, AAAI 96. Part 1 (of 2) - Portland, OR, USA
Duration: Aug 4 1996Aug 8 1996

Other

OtherProceedings of the 1996 13th National Conference on Artificial Intelligence, AAAI 96. Part 1 (of 2)
CityPortland, OR, USA
Period8/4/968/8/96

ASJC Scopus subject areas

  • Software

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