DocumentCode
1637890
Title
Regular language inference using evolving neural networks
Author
Lindgren, Kristian ; Nilsson, A. ; Nordahl, Mats G. ; Råde, Ingrid
Author_Institution
Inst. of Phys. Resource Theory, Chalmers Univ. of Technol., Goteborg, Sweden
fYear
1992
fDate
6/6/1992 12:00:00 AM
Firstpage
75
Lastpage
86
Abstract
Regular language inference is studied using evolving recurrent neural networks that may change in size through mutations. The scaling of the learning time when information theoretic properties of the test problems are varied is also investigated
Keywords
finite automata; formal languages; inference mechanisms; information theory; learning (artificial intelligence); recurrent neural nets; evolving neural networks; finite automata; formal languages; information theoretic properties; learning time; regular language inference; Algorithm design and analysis; Automata; Genetic algorithms; Genetic mutations; Heuristic algorithms; Inference algorithms; Neural networks; Recurrent neural networks; Statistical distributions; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Combinations of Genetic Algorithms and Neural Networks, 1992., COGANN-92. International Workshop on
Conference_Location
Baltimore, MD
Print_ISBN
0-8186-2787-5
Type
conf
DOI
10.1109/COGANN.1992.273947
Filename
273947
Link To Document