DocumentCode :
2713889
Title :
Basic Technologies for Knowledge Transfer in Intelligent Systems
Author :
Buchtala, Oliver ; Sick, Bernhard
Author_Institution :
Fac. of Comput. Sci. & Math., Passau Univ.
fYear :
2007
fDate :
1-5 April 2007
Firstpage :
251
Lastpage :
258
Abstract :
Knowledge transfer is one of the most important mechanisms of human evolution. The ontogeny of humans enables them to act efficiently in a very dynamic environment. Thus, it would be highly desirable to enable "intelligent" artificial systems to behave in a similar way. This article introduces basic technologies that are needed for that purpose. With these technologies - components of a future knowledge transfer toolbox - it is possible to detect novel concepts that arise in the input space of a classifier or existing classification rules that become obsolete. Then, prototypes of new rules can be created automatically using an on-line clustering mechanism. These prototypes are compared to already existing rules, rated, and eventually accepted or discarded. In case of acceptance, a human expert labels the rules which are then both integrated into the "own" classifier and sent to other classifiers. Thus, knowledge transfer between "intelligent" artificial systems becomes possible and the overall system is provided with a new kind of self-optimization ability
Keywords :
artificial life; biology computing; evolution (biological); knowledge based systems; human evolution; intelligent artificial systems; intelligent system; knowledge transfer; online clustering; ontogeny; Artificial intelligence; Detectors; Educational institutions; Humans; Intelligent agent; Intelligent robots; Intelligent systems; Knowledge transfer; Prototypes; Space technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Life, 2007. ALIFE '07. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0701-X
Type :
conf
DOI :
10.1109/ALIFE.2007.367804
Filename :
4218894
Link To Document :
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