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＜電子ブック＞
A Future for Knowledge Acquisition : 8th European Knowledge Acquisition Workshop, EKAW'94, Hoegaarden, Belgium, September 26 - 29, 1994. Proceedings / edited by Luc Steels, Guus Schreiber, Walter Van de Velde
(Lecture Notes in Artificial Intelligence. ISSN:29459141 ; 867)

版	1st ed. 1994.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	1994
本文言語	英語
大きさ	XII, 424 p : online resource
著者標目	Steels, Luc editor Schreiber, Guus editor Van de Velde, Walter editor SpringerLink (Online service)
件　名	LCSH:Artificial intelligence FREE:Artificial Intelligence
一般注記	CML: The commonKADS conceptual modelling language -- Evaluating a formal modelling language -- A comparison of two approaches to model-based knowledge acquisition -- Agent-based knowledge acquisition -- Beyond the knowledge level: Descriptions of rational behavior for sharing and reuse -- Local patching produces compact knowledge bases -- Components of problem solving and types of problems -- On a role of problem solving methods in knowledge acquisition -- Modeling plan recognition for decision support -- CUE: Ontology based knowledge acquisition -- KARO: An integrated environment for reusing ontologies -- From verification to modelling guidelines -- AFORIZM approach: Creating situations to facilitate expertise transfer -- How to combine data abstraction and model refinement: A methodological contribution in MACAO -- User centered knowledge-based system design: a formal modelling approach -- Validating at early stages with a causal simulation tool -- The SBF framework, 1989–1994: From applications to workplaces -- Applying the REKAP methodology to situation assessment -- Integration of learning into a knowledge modelling framework -- Knowledge level model of a configurable learning system -- Reflective, self-adaptive problem solvers This volume comprises a selection of the key papers presented at the Eighth European Knowledge Acquisition Workshop (EKAW '94), held in Hoegaarden, Belgium in September 1994. The book demonstrates that work in the mainstream of knowledge acquisition leads to useful practical results and puts the knowledge acquisition enterprise in a broader theoretical and technological context. The 21 revised full papers are carefully selected key contributions; they address knowledge modelling frameworks, the identification of generic components, methodology aspects, and architectures and applications. The volume opens with a substantial preface by the volume editors surveying the contents HTTP:URL=https://doi.org/10.1007/3-540-58487-0

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