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» Function Approximation With XCS: Hyperellipsoidal Conditions...
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TEC
2008
115views more  TEC 2008»
13 years 4 months ago
Function Approximation With XCS: Hyperellipsoidal Conditions, Recursive Least Squares, and Compaction
An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 8 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
13 years 5 months ago
Recursive least squares and quadratic prediction in continuous multistep problems
XCS with computed prediction, namely XCSF, has been recently extended in several ways. In particular, a novel prediction update algorithm based on recursive least squares and the ...
Daniele Loiacono, Pier Luca Lanzi