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» Evolving heuristics with genetic programming
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CEC
2010
IEEE
13 years 11 months ago
Evolving programs with parameters and loops
At the current state of the art, genetic programs do not contain two constructs that commonly occur in programs written by humans, that is, loops and functions with parameters. In ...
Gayan Wijesinghe, Victor Ciesielski
EUROGP
2005
Springer
122views Optimization» more  EUROGP 2005»
14 years 3 months ago
Evolution of Robot Controller Using Cartesian Genetic Programming
Abstract. Cartesian Genetic Programming is a graph based representation that has many benefits over traditional tree based methods, including bloat free evolution and faster evolu...
Simon Harding, Julian F. Miller
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
14 years 3 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
GECCO
2009
Springer
190views Optimization» more  GECCO 2009»
14 years 1 months ago
Genetic programming for protein related text classification
Since the genomics revolution, bioinformatics has never been so popular. Many researchers have investigated with great success the use of evolutionary computation in bioinformatic...
Marc Segond, Cyril Fonlupt, Denis Robilliard
IPPS
1999
IEEE
14 years 2 months ago
Distributed Scheduling with Decomposed Optimization Criterion: Genetic Programming Approach
Abstract. A new approach to develop parallel and distributed scheduling algorithms for multiprocessor systems is proposed. Its main innovation lies in evolving a decomposition of t...
Franciszek Seredynski, Jacek Koronacki, Cezary Z. ...