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CEC
2005
IEEE
13 years 7 months ago
XCS with computed prediction in continuous multistep environments
We apply XCS with computed prediction (XCSF) to tackle multistep reinforcement learning problems involving continuous inputs. In essence we use XCSF as a method of generalized rein...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
GECCO
2005
Springer
13 years 11 months ago
XCS with computed prediction in multistep environments
XCSF extends the typical concept of learning classifier sys
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
13 years 6 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
GECCO
2005
Springer
111views Optimization» more  GECCO 2005»
13 years 11 months ago
XCS with eligibility traces
The development of the XCS Learning Classifier System has produced a robust and stable implementation that performs competitively in direct-reward environments. Although investig...
Jan Drugowitsch, Alwyn Barry
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
13 years 9 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...