Flexible and scalable query access planning using an AI planner

Author

Ambite, José Luis ; Knoblock, Craig A.

Author_Institution

Inf. Sci. Inst., Univ. of Southern California, Marina del Rey, CA, USA

fYear

1997

fDate

35738

Firstpage

132

Lastpage

139

Abstract

Planning by rewriting (PBR) is a new paradigm for efficient high-quality planning that exploits plan rewriting rules and efficient local search techniques to transform an easy-to-generate, but possibly suboptimal, initial plan into a low-cost plan. In this paper, we show in detail the application of the general framework to query planning in distributed environments. As a result, we obtain an scalable and flexible query planner for use in an information mediator

Keywords

deductive databases; distributed databases; planning (artificial intelligence); query processing; rewriting systems; search problems; AI planner; distributed environments; efficient high-quality planning; flexibility; information mediator; local search techniques; low-cost plan; planning by rewriting; query access planning; rewriting rules; scalability; suboptimal initial plan; Artificial intelligence; Bioreactors; Computer science; Data models; Interleaved codes; Iterative algorithms; Learning systems; Object oriented modeling; Process planning; Search methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge and Data Engineering Exchange Workshop, 1997. Proceedings

Conference_Location

Newport Beach, CA

Print_ISBN

0-8186-8230-2

Type

conf

DOI

10.1109/KDEX.1997.629854

Filename

629854