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» Optimization via Parameter Mapping with Genetic Programming
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GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
15 years 3 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...
GECCO
2005
Springer
142views Optimization» more  GECCO 2005»
15 years 3 months ago
Genetic programming: parametric analysis of structure altering mutation techniques
We hypothesize that the relationship between parameter settings, speci cally parameters controlling mutation, and performance is non-linear in genetic programs. Genetic programmin...
Alan Piszcz, Terence Soule
FLAIRS
2006
14 years 11 months ago
Genetic Programming: Analysis of Optimal Mutation Rates in a Problem with Varying Difficulty
In this paper we test whether a correlation exists between the optimal mutation rate and problem difficulty. We find that the range of optimal mutation rates is inversely proporti...
Alan Piszcz, Terence Soule
68
Voted
EUROGP
1999
Springer
151views Optimization» more  EUROGP 1999»
15 years 1 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
78
Voted

Publication
285views
15 years 1 months ago
Center of mass encoding: a self-adaptive representation with adjustable redundancy for real-valued parameters
In this paper we describe a new class of representations for realvalued parameters called Center of Mass Encoding (CoME). CoME is based on variable length strings, it is self-adap...
Claudio Mattiussi, Peter Dürr, Dario Floreano