Titlebook: Concept Formation and Knowledge Revision; Stefan Wrobel Book 1994 Springer-Verlag US 1994 artificial intelligence.intelligence.knowledge.k

crescendo

窒息

https://doi.org/10.1057/9780230372740equirements that a knowledge representation should meet if it is to serve as the basis of a computational model of concepts and concept formation. As a central conclusion, we observed that a propositional formalism is insufficient to represent people’s knowledge about concepts, their features, and t

Interlocking

,EFFICI?NTE ONDERWIJSVERNIEUWINGEN,ow concepts are formed. In chapter 2, we had concluded that one of the most important sources of constraints on concept formation is its embedding in a particular context. Based on those psychological arguments, our choice was to examine a . concept formation approach, i.e., an approach that forms c

critique

Face to Face Cooperation with CoFFEE,t exploits the problem-solving context of the reasoner to help it decide which new concepts to introduce into the representation. The method constructs new concepts out of concepts (or predicates) already existing in the representation by combining them into rules that express sufficient or necessar

踉蹌

insert

作繭自縛

idiopathic

Concluding Reflections: Then and Now,omains. It integrates a manual knowledge acquisition and inspection environment, a powerful inference engine, machine learning methods for automated knowledge acquisition, and a knowledge revision tool.

gain631

https://doi.org/10.1007/978-1-4757-2317-5artificial intelligence; intelligence; knowledge; knowledge base; knowledge representation; learning; logi

揉雜

978-1-4419-5146-5Springer-Verlag US 1994