Organizing Plan Libraries in Subsumption Hierarchies: Specificity Based Plan Selection

Abstract

As the number of plans in a plan library grows, the importance of selecting a plan efficiently also increases. Previous planners have not addressed this issue in great detail, because they typically had only tens of plans - as domain models grow more and more specialized, and planners incorporate new macro-operators through learning, plan libraries can become more than a magnitude greater in size. This paper addresses the issue of organizing plan libraries in specificity based hierarchies. In particular, we look at how a plan library can be represented in a frame-based KL-ONE style system. Such systems offer powerful mechanisms to handle dynamically changing knowledge bases. In particular, the subsumption classifier mechanism in such systems, offers a simple and efficient means of indexing new plans and goals into the hierarchy. We illustrate the feasibility of this approach by using examples from an implemented system, and describe some of the other advantages that accrue from the use of such a framework for organizing large plan libraries.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADA248711

Entities

People

  • Cecil Paris
  • Ramesh Patil
  • Vibhu Mittal
  • William Swartout

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computational Complexity
  • Computers
  • Discrimination
  • Expert Systems
  • Hash Tables
  • Hierarchies
  • Language
  • Learning
  • Machine Learning
  • Sequences
  • Specialization
  • Specifications
  • Words (Language)

Readers

  • Artificial Intelligence