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» Function choice, resiliency and growth in genetic programmin...
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ICRA
1998
IEEE
147views Robotics» more  ICRA 1998»
13 years 9 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
BMCBI
2007
145views more  BMCBI 2007»
13 years 5 months ago
Colony size measurement of the yeast gene deletion strains for functional genomics
Background: Numerous functional genomics approaches have been developed to study the model organism yeast, Saccharomyces cerevisiae, with the aim of systematically understanding t...
Negar Memarian, Matthew Jessulat, Javad Alirezaie,...
ECAI
2010
Springer
13 years 6 months ago
Nested Monte-Carlo Expression Discovery
Nested Monte-Carlo search is a general algorithm that gives good results in single player games. Genetic Programming evaluates and combines trees to discover expressions that maxim...
Tristan Cazenave
GECCO
1999
Springer
167views Optimization» more  GECCO 1999»
13 years 9 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
2008
Springer
201views Optimization» more  GECCO 2008»
13 years 6 months ago
Advanced techniques for the creation and propagation of modules in cartesian genetic programming
The choice of an appropriate hardware representation model is key to successful evolution of digital circuits. One of the most popular models is cartesian genetic programming, whi...
Paul Kaufmann, Marco Platzner