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GECCO
1999
Springer
167views Optimization» more  GECCO 1999»
14 years 29 days 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
133views Optimization» more  GECCO 2008»
13 years 9 months ago
Using feature-based fitness evaluation in symbolic regression with added noise
Symbolic regression is a popular genetic programming (GP) application. Typically, the fitness function for this task is based on a sum-of-errors, involving the values of the depe...
Janine H. Imada, Brian J. Ross
KBSE
2007
IEEE
14 years 3 months ago
Nighthawk: a two-level genetic-random unit test data generator
Randomized testing has been shown to be an effective method for testing software units. However, the thoroughness of randomized unit testing varies widely according to the settin...
James H. Andrews, Felix Chun Hang Li, Tim Menzies
3DIM
2005
IEEE
14 years 2 months ago
Fitting of 3D Circles and Ellipses Using a Parameter Decomposition Approach
Many optimization processes encounter a problem in efficiently reaching a global minimum or a near global minimum. Traditional methods such as Levenberg-Marquardt algorithm and t...
Xiaoyi Jiang, Da-Chuan Cheng
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
14 years 11 days ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...