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Very Large Planner-Type Data Bases.
MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB
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This paper describes the implementation of a typical data-base manager for an AI language like Planner, Conniver, or QA4, and some proposed extensions for applications involving greater quantities of data than usual. The extensions are concerned with data bases involving several active and potentially active sub-data bases, or contexts. The major mechanisms discussed are the use of contexts as packets of data with free variables and indexing data according to the contexts they appear in. The paper also defends the Planner approach to data representation against some more recent proposals. Author
APPROVED FOR PUBLIC RELEASE