Sciweavers

Share
EH
2004
IEEE
107views Hardware» more  EH 2004»
9 years 5 months ago
Evolving Digital Circuits using Multi Expression Programming
Multi Expression Programming (MEP) is a Genetic Programming (GP) variant that uses linear chromosomes for solution encoding. A unique MEP feature is its ability of encoding multipl...
Mihai Oltean, Crina Grosan
EH
2004
IEEE
125views Hardware» more  EH 2004»
9 years 5 months ago
Routine High-Return Human-Competitive Evolvable Hardware
This paper reviews the use of genetic programming as an automated invention machine for the synthesis of both the topology and sizing of analog electrical circuits. The paper focu...
John R. Koza, Martin A. Keane, Matthew J. Streeter
GECCO
2009
Springer
190views Optimization» more  GECCO 2009»
9 years 5 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
GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
9 years 5 months ago
A GP neutral function for the artificial ANT problem
This paper introduces a function that increases the amount of neutrality (inactive code in Genetic Programming) for the Artificial Ant Problem. The objective of this approach is t...
Esteban Ricalde, Katya Rodríguez-Váz...
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
9 years 5 months ago
Combining bond-graphs with genetic programming for unified/automated design of mechatronic or multi domain dynamic systems
The multi domain nature of a mechatronic system makes it difficult to model using a single modeling technique over the whole system as varying sets of system variables are require...
Saheeb Ahmed Kayani, Muhammad Afzaal Malik
GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
9 years 5 months ago
Diverse committees vote for dependable profits
Stock selection for hedge fund portfolios is a challenging problem for Genetic Programming (GP) because the markets (the environment in which the GP solution must survive) are dyn...
Wei Yan, Christopher D. Clack
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
9 years 5 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
9 years 5 months ago
A new crossover technique for Cartesian genetic programming
Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped ...
Janet Clegg, James Alfred Walker, Julian Francis M...
EUROGP
2007
Springer
145views Optimization» more  EUROGP 2007»
9 years 5 months ago
GP Classifier Problem Decomposition Using First-Price and Second-Price Auctions
This work details an auction-based model for problem decomposition in Genetic Programming classification. The approach builds on the population-based methodology of Genetic Progra...
Peter Lichodzijewski, Malcolm I. Heywood
GECCO
2010
Springer
218views Optimization» more  GECCO 2010»
9 years 5 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
books