A Future for Knowledge Acquisition
Editat de Luc Steels, Guus Schreiber, Walter van de Veldeen Limba Engleză Paperback – 14 sep 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.
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Specificații
ISBN-13: 9783540584872
ISBN-10: 3540584870
Pagini: 436
Ilustrații: XII, 424 p.
Dimensiuni: 155 x 235 x 24 mm
Greutate: 0.66 kg
Ediția:1994
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540584870
Pagini: 436
Ilustrații: XII, 424 p.
Dimensiuni: 155 x 235 x 24 mm
Greutate: 0.66 kg
Ediția:1994
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
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.