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dc.contributor.authorEichhoff, Julian R.
dc.contributor.authorRoller, Dieter
dc.contributor.editorPlödereder, E.
dc.contributor.editorGrunske, L.
dc.contributor.editorSchneider, E.
dc.contributor.editorUll, D.
dc.date.accessioned2017-07-26T10:59:07Z
dc.date.available2017-07-26T10:59:07Z
dc.date.issued2014
dc.identifier.isbn978-3-88579-626-8
dc.identifier.issn1617-5468
dc.description.abstractThis paper outlines the problem of efficiently formalizing functional design rationale in form of graph-rewriting production rules. It is argued that genetic programming provides a feasible machine learning approach to this.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofInformatik 2014
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-232
dc.titleApproach to learning production rules for grammar-based functional designen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages1977-1978
mci.conference.locationStuttgart
mci.conference.date22.-26. September 2014


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