Title :
Learning in the large: case-based software systems design
Author :
Rubin, Stuart H.
Author_Institution :
US Naval Ocean Syst. Center, San Diego, CA, USA
Abstract :
The author describes a novel approach to the development of a knowledge-based software assistant (KBSA) by applying artificial intelligence in an integrated rather than a supportive role; that is, an attempt is made to offer a framework for unifying case-based reasoning (CBR) with object-oriented rule-based systems, for unifying man-machine systems with learning, and for unifying object-oriented analogical reasoning with constrained search. The technique is called constrained-set generalization (CSG). The CSG technique emphasizes the importance of the man-machine interface in learning heuristics. It also purports a computational theory of creativity, which is based upon the object-oriented concept of set analogs. CSG has been applied to the problem of generalizing and reusing software fragments
Keywords :
inference mechanisms; knowledge based systems; learning systems; object-oriented programming; software reusability; user interfaces; artificial intelligence; case-based reasoning; constrained search; constrained-set generalization; creativity; knowledge-based software assistant; learning heuristics; machine learning; man-machine interface; object-oriented analogical reasoning; object-oriented rule-based systems; user interface; Artificial intelligence; Humans; Knowledge acquisition; Oceans; Problem-solving; Prototypes; Software design; Software prototyping; Software systems; Sun;
Conference_Titel :
Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on
Conference_Location :
Charlottesville, VA
Print_ISBN :
0-7803-0233-8
DOI :
10.1109/ICSMC.1991.169645