• Medientyp: Bericht; E-Book
  • Titel: Learning and Clustering Plan Abstractions to Improve Hierarchical Planning
  • Beteiligte: Bergmann, Ralph [Verfasser:in]
  • Erschienen: KLUEDO - Publication Server of University of Kaiserslautern-Landau (RPTU), 1999
  • Sprache: Englisch
  • Schlagwörter: explanation-based learning ; Knowledge Acquisition ; case-based problem solving ; Abstraction
  • Entstehung:
  • Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Beschreibung: Hierachical planning can be improved by explanation-based learning (EBL) of abstract plans from detailed, successfully solved planning problems. Abstract plans, expressed in well-established terms of the domain, serve as useful problem decompositions which can drastically reduce the planning complexity. The learned plan abstraction must be valid for a class of planning cases rather than for a single case, to ensure their successful application in a larger spectrum of new situations. A hierarchical organization of the newly learned knowledge must be archieved to overcome the utility problem in EBL. This paper presents a new formal model of shared plan abstraction and the closely related explanation-based procedure S-PABS. Unlike other apporaches to plan abstraction, our model allows a total different terminology to be introduced at the abstract level. Finally, an unsupervised incremental procedure for constructing a hierachy of shared abstract plans is proposed, as a kind of concept formation over explanations.
  • Zugangsstatus: Freier Zugang