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GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
13 years 12 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
MFCS
2004
Springer
13 years 10 months ago
Approximating Boolean Functions by OBDDs
In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximatin...
Andre Gronemeier
UPP
2004
Springer
13 years 10 months ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
ICTAI
2009
IEEE
13 years 12 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...
ICALP
2001
Springer
13 years 9 months ago
Separating Quantum and Classical Learning
We consider a model of learning Boolean functions from quantum membership queries. This model was studied in [26], where it was shown that any class of Boolean functions which is i...
Rocco A. Servedio