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EC
1998
134views ECommerce» more  EC 1998»
13 years 7 months ago
Schema Theory for Genetic Programming with One-Point Crossover and Point Mutation
In this paper we first review the main results obtained in the theory of schemata in Genetic Programming (GP) emphasising their strengths and weaknesses. Then we propose a new, s...
Riccardo Poli, William B. Langdon
GECCO
2004
Springer
105views Optimization» more  GECCO 2004»
14 years 27 days ago
Softening the Structural Difficulty in Genetic Programming with TAG-Based Representation and Insertion/Deletion Operators
In a series of papers [3-8], Daida et. al. highlighted the difficulties posed to Genetic Programming (GP) by the complexity of the structural search space, and attributed the probl...
Nguyen Xuan Hoai, Robert I. McKay
EUROGP
1999
Springer
151views Optimization» more  EUROGP 1999»
13 years 11 months ago
Phenotype Plasticity in Genetic Programming: A Comparison of Darwinian and Lamarckian Inheritance Schemes
Abstract We consider a form of phenotype plasticity in Genetic Programming (GP). This takes the form of a set of real-valued numerical parameters associated with each individual, a...
Anna Esparcia-Alcázar, Ken Sharman
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
13 years 11 months ago
Improving GP classifier generalization using a cluster separation metric
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Ashley George, Malcolm I. Heywood
GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving recurrent models using linear GP
Turing complete Genetic Programming (GP) models introduce the concept of internal state, and therefore have the capacity for identifying interesting temporal properties. Surprisin...
Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywoo...