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.
|Author:||Ralph Bergmann, Wolfgang Wilke|
|URN (permanent link):||urn:nbn:de:hbz:386-kluedo-1664|
|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|
PARIS is a fully implemented system which integrates learning and problem solving (planning).
|Faculties / Organisational entities:||Fachbereich Informatik|
|DDC-Cassification:||004 Datenverarbeitung; Informatik|