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162
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CORR
2006
Springer
153views Education» more  CORR 2006»
15 years 3 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
15 years 9 months ago
Learning Biped Locomotion from First Principles on a Simulated Humanoid Robot Using Linear Genetic Programming
We describe the first instance of an approach for control programming of humanoid robots, based on evolution as the main adaptation mechanism. In an attempt to overcome some of th...
Krister Wolff, Peter Nordin
117
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GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
15 years 10 months ago
Hierarchical genetic programming based on test input subsets
Crucial to the more widespread use of evolutionary computation techniques is the ability to scale up to handle complex problems. In the field of genetic programming, a number of d...
David Jackson
GECCO
2003
Springer
117views Optimization» more  GECCO 2003»
15 years 9 months ago
Improving Evolvability of Genetic Parallel Programming Using Dynamic Sample Weighting
Abstract. This paper investigates the sample weighting effect on Genetic Parallel Programming (GPP) that evolves parallel programs to solve the training samples captured directly f...
Sin Man Cheang, Kin-Hong Lee, Kwong-Sak Leung
123
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GECCO
2000
Springer
178views Optimization» more  GECCO 2000»
15 years 7 months ago
Fitness Sharing in Genetic Programming
This paper investigates fitness sharing in genetic programming. Implicit fitness sharing is applied to populations of programs. Three treatments are compared: raw fitness, pure fi...
Robert I. McKay