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» Function Approximation With XCS: Hyperellipsoidal Conditions...
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TEC
2008
115views more  TEC 2008»
14 years 9 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»
15 years 1 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»
14 years 10 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