DocumentCode :
2409786
Title :
Case-based introspective learning
Author :
Shi, Zhongzhi ; Zhang, Sulan
Author_Institution :
Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing, China
fYear :
2005
fDate :
8-10 Aug. 2005
Firstpage :
43
Lastpage :
48
Abstract :
Introspective learning, as a method to improve the learning efficiency, has become an active area of research. In this paper, introspective learning and a general introspective learning mode are discussed. Some related problems such as meta-level reasoning, taxonomy of failure, and the relation between case-based reasoning and introspective learning are represented. Based on the importance of case-based reasoning in introspective learning, a case representation and case retrieval mechanism appropriate to introspective learning are described in detail.
Keywords :
case-based reasoning; learning (artificial intelligence); case representation; case retrieval; case-based introspective learning; case-based reasoning; failure taxonomy; metalevel reasoning; Computers; Failure analysis; Intelligent systems; Learning systems; Machine learning; Performance analysis; Problem-solving; Psychology; Taxonomy; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics, 2005. (ICCI 2005). Fourth IEEE Conference on
Print_ISBN :
0-7803-9136-5
Type :
conf
DOI :
10.1109/COGINF.2005.1532614
Filename :
1532614
Link To Document :
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