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» Unsupervised Problem Decomposition Using Genetic Programming
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GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
15 years 3 months ago
Evolving problem heuristics with on-line ACGP
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...
Cezary Z. Janikow
CEC
2010
IEEE
14 years 10 months ago
Defining locality in genetic programming to predict performance
Abstract-- A key indicator of problem difficulty in evolutionary computation problems is the landscape's locality, that is whether the genotype-phenotype mapping preserves nei...
Edgar Galván López, James McDermott,...
CEC
2009
IEEE
15 years 4 months ago
Representation and structural biases in CGP
— An evolutionary algorithm automatically discovers suitable solutions to a problem, which may lie anywhere in a large search space of candidate solutions. In the case of Genetic...
Andrew J. Payne, Susan Stepney
ICASSP
2011
IEEE
14 years 1 months ago
Multiple kernel nonnegative matrix factorization
Kernel nonnegative matrix factorization (KNMF) is a recent kernel extension of NMF, where matrix factorization is carried out in a reproducing kernel Hilbert space (RKHS) with a f...
Shounan An, Jeong-Min Yun, Seungjin Choi
82
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GECCO
2008
Springer
113views Optimization» more  GECCO 2008»
14 years 10 months ago
Genetic programming based automatic gait generation for quadruped robots
This paper introduces a new approach to develop a fast gait for quadruped robot using genetic programming (GP). Several recent approaches have focused on the genetic algorithm (GA...
Kisung Seo, Soohwan Hyun