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GECCO
2005
Springer
14 years 1 months ago
Function choice, resiliency and growth in genetic programming
In this paper we examine how the choice of functions in a genetic program (GP) affects the rate of code growth and the development of resilient individuals. We find that functio...
Sireesha Besetti, Terence Soule
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 11 months ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
EUROGP
2001
Springer
105views Optimization» more  EUROGP 2001»
14 years 5 days ago
Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems
Abstract. In this paper we continue our study on adaptive genetic programming. We use Stepwise Adaptation of Weights (saw) to boost performance of a genetic programming algorithm o...
Jeroen Eggermont, Jano I. van Hemert
EUROGP
2010
Springer
172views Optimization» more  EUROGP 2010»
13 years 11 months ago
Geometric Differential Evolution on the Space of Genetic Programs
Abstract. Geometric Differential Evolution (GDE) is a very recently introduced formal generalization of traditional Differential Evolution (DE) that can be used to derive specific ...
Alberto Moraglio, Sara Silva
EUROGP
2008
Springer
128views Optimization» more  EUROGP 2008»
13 years 9 months ago
Hardware Accelerators for Cartesian Genetic Programming
A new class of FPGA-based accelerators is presented for Cartesian Genetic Programming (CGP). The accelerators contain a genetic engine which is reused in all applications. Candidat...
Zdenek Vasícek, Lukás Sekanina