Title :
Two-sided hypotheses generation for abductive analogical reasoning
Author_Institution :
NTT Commun. Sci. Labs., Soraku, Japan
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;
Conference_Titel :
Tools with Artificial Intelligence, 1999. Proceedings. 11th IEEE International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7695-0456-6
DOI :
10.1109/TAI.1999.809779