On the learnability of R.E. languages from good examples

Authors: 
Jain, Sanjay
Lange, Steffen
Nessel, Jochen
Year: 
1997
Language: 
English
Abstract: 
The present paper investigates identification of indexed families of recursively enumerable languages from good examples. In the context of class preserving learning from good text examples, it is shown that the notions of finite and limit identification coincide. On the other hand, these two criteria are different in the context of class comprising learning from good text examples. In the context of learning from good informant examples, finite and limit identification criteria differ for both class preserving and class comprising cases. The above results resolve an open question posed by Lange, Nessel and Wiehagen in a similar study about indexed families of recursive languages.
Appeared / Erschienen in: 
Proc. 8th Int. Workshop on Algorithmic Learning Theory (ALT'97), Lecture Notes in Artificial Intelligence 1316, Springer-Verlag, 1997, S. 32-47
Pubdate / Erscheinungsdatum: 
1997
Pages / Seitenanzahl: 
16