DocumentCode
3373845
Title
Two-sided hypotheses generation for abductive analogical reasoning
Author
Abe, Akinori
Author_Institution
NTT Commun. Sci. Labs., Soraku, Japan
fYear
1999
fDate
1999
Firstpage
145
Lastpage
152
Abstract
In general, if a knowledge base lacks the necessary knowledge, abductive reasoning cannot explain an observation. Therefore, it is necessary to generate missing hypotheses. CMS can generate missing hypotheses, but it can only generate short-cut hypotheses or hypotheses that will not be placed on real leaves. That is, the inference path is incomplete (truncated), so that abduction is not complete. The inference proposed tries to generate missing hypotheses that are placed on the middle of the inference path by both abductive inference and deductive inference using analogical mapping. As a result, the inference can generate missing hypotheses even on the middle of the inference path
Keywords
case-based reasoning; uncertainty handling; CMS; abductive analogical reasoning; analogical mapping; deductive inference; inference path; knowledge base; missing hypotheses; two-sided hypotheses generation; Artificial intelligence; Collision mitigation; Fuels; Horses; Inference mechanisms; Laboratories;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 1999. Proceedings. 11th IEEE International Conference on
Conference_Location
Chicago, IL
ISSN
1082-3409
Print_ISBN
0-7695-0456-6
Type
conf
DOI
10.1109/TAI.1999.809779
Filename
809779
Link To Document