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GECCO
2004
Springer
115views Optimization» more  GECCO 2004»
14 years 1 months ago
Robotic Control Using Hierarchical Genetic Programming
In this paper, we compare the performance of hierarchical GP methods (Automatically Defined Functions, Module Acquisition, Adaptive Representation through Learning) with the canon...
Marcin L. Pilat, Franz Oppacher
NAR
2006
96views more  NAR 2006»
13 years 7 months ago
mtDB: Human Mitochondrial Genome Database, a resource for population genetics and medical sciences
The mitochondrial genome, contained in the subcellular mitochondrial network, encodes a small number of peptides pivotal for cellular energy production. Mitochondrialgenesarehighl...
Max Ingman, Ulf Gyllensten
ICANNGA
2009
Springer
203views Algorithms» more  ICANNGA 2009»
14 years 2 months ago
NEAT in HyperNEAT Substituted with Genetic Programming
In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights. We compare usage of original HyperNEAT algorithm w...
Zdenek Buk, Jan Koutník, Miroslav Snorek
GECCO
1999
Springer
167views Optimization» more  GECCO 1999»
13 years 12 months ago
A Biologically Inspired Fitness Function for Robotic Grasping
This paper describes the innovative use of genetic programming (GP) to solve the grasp synthesis problem for multifingered robot hands. The goal of our algorithm is to select a Ò...
J. Jaime Fernandez, Ian D. Walker
GECCO
2010
Springer
218views Optimization» more  GECCO 2010»
13 years 11 months ago
Cartesian genetic programming
This paper presents a new form of Genetic Programming called Cartesian Genetic Programming in which a program is represented as an indexed graph. The graph is encoded in the form o...
Julian Francis Miller, Simon L. Harding