Learning Abstract Planning Cases

  • In this paper, we propose the PARIS approach for improving complex problem solving by learning from previous cases. In this approach, abstract planning cases are learned from given concrete cases. For this purpose, we have developed a new abstraction methodology that allows to completely change the representation language of a planning case, when the concrete and abstract languages are given by the user. Furthermore, we present a learning algorithm which is correct and complete with respect to the introduced model. An empirical study in the domain of process planning in mechanical engineering shows significant improvements in planning efficiency through learning abstract cases while an explanation-based learning method only causes a very slight improvement.

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Metadaten
Author:Ralph Bergmann, Wolfgang Wilke
URN (permanent link):urn:nbn:de:hbz:386-kluedo-1664
Document Type:Preprint
Language of publication:English
Year of Completion:1999
Year of Publication:1999
Publishing Institute:Technische Universität Kaiserslautern
Tag:explanation-based learning; learning system ; problem solving
Note:
PARIS is a fully implemented system which integrates learning and problem solving (planning).
Faculties / Organisational entities:Fachbereich Informatik
DDC-Cassification:004 Datenverarbeitung; Informatik

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