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A brief history of learning classifier systems: from CS-1 to XCS and its variants
Authors
A Fernández
A Fraser
+56 more
A Orriols-Puig
A Tomlinson
AL Samuel
AL Samuel
B Farley
C Fernando
C Shannon
C Stone
D Cliff
E Bernado Mansilla
G Box
H Dam
J Casillas
J Greensmith
J Hoffmann
J Seward
J Timmis
JD Farmer
JH Holland
JH Holland
JH Holland
L Booker
L Bull
L Bull
L Bull
L Castro De
Larry Bull
M Iqbal
M Iqbal
M Studley
MV Butz
MV Butz
MV Butz
MV Butz
MV Butz
MV Butz
MV Butz
N Coufal
P Frey
P Stalph
P Stalph
P-L Lanzi
P-L Lanzi
P-L Lanzi
R Preen
R Smith
R Smith
R Sutton
R Tibshirani
R Urbanowicz
S Becker
S Vijayakumar
SW Wilson
SW Wilson
SW Wilson
W Schultz
Publication date
26 September 2015
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
Abstract
© 2015, Springer-Verlag Berlin Heidelberg. The direction set by Wilson’s XCS is that modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Such searching typically takes place within the restricted space of co-active rules for efficiency. This paper gives an overview of the evolution of Learning Classifier Systems up to XCS, and then of some of the subsequent developments of Wilson’s algorithm to different types of learning
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Last time updated on 08/06/2020
Crossref
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info:doi/10.1007%2Fs12065-015-...
Last time updated on 05/06/2019