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GECCO
2009
Springer
164views Optimization» more  GECCO 2009»
13 years 2 months ago
Solving iterated functions using genetic programming
An iterated function f(x) is a function that when composed with itself, produces a given expression f(f(x))=g(x). Iterated functions are essential constructs in fractal theory and...
Michael D. Schmidt, Hod Lipson
ICRA
1998
IEEE
147views Robotics» more  ICRA 1998»
13 years 8 months ago
Biologically Inspired Robot Grasping Using Genetic Programming
This paper describes the innovative use of a genetic algorithm to solve the grasp synthesis problem for multifingered robot hands. The goal of our algorithm is to select a `best&#...
Jaime J. Fernandez, Ian D. Walker
GPEM
2010
180views more  GPEM 2010»
13 years 3 months ago
Developments in Cartesian Genetic Programming: self-modifying CGP
Abstract Self-Modifying Cartesian Genetic Programming (SMCGP) is a general purpose, graph-based, developmental form of Genetic Programming founded on Cartesian Genetic Programming....
Simon Harding, Julian F. Miller, Wolfgang Banzhaf
GECCO
2007
Springer
293views Optimization» more  GECCO 2007»
13 years 10 months ago
Solving the artificial ant on the Santa Fe trail problem in 20, 696 fitness evaluations
In this paper, we provide an algorithm that systematically considers all small trees in the search space of genetic programming. These small trees are used to generate useful subr...
Steffen Christensen, Franz Oppacher
GECCO
2007
Springer
151views Optimization» more  GECCO 2007»
13 years 10 months ago
Solving real-valued optimisation problems using cartesian genetic programming
Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) have been applied to realvalued function optimisation. Both of these techniques directly evolve th...
James Alfred Walker, Julian Francis Miller