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ESANN
2006
13 years 9 months ago
Using distributed genetic programming to evolve classifiers for a brain computer interface
The objective of this paper is to illustrate the application of genetic programming to evolve classifiers for multi-channel time series data. The paper shows how high performance d...
Eva Alfaro-Cid, Anna Esparcia-Alcázar, Ken ...
EUROGP
2005
Springer
104views Optimization» more  EUROGP 2005»
14 years 1 months ago
mGGA: The meta-Grammar Genetic Algorithm
A novel Grammatical Genetic Algorithm, the meta-Grammar Genetic Algorithm (mGGA) is presented. The mGGA borrows a grammatical representation and the ideas of modularity and reuse f...
Michael O'Neill, Anthony Brabazon
GECCO
2005
Springer
142views Optimization» more  GECCO 2005»
14 years 1 months ago
Goal-oriented preservation of essential genetic information by offspring selection
This contribution proposes an enhanced and generic selection model for Genetic Algorithms (GAs) and Genetic Programming (GP) which is able to preserve the alleles which are part o...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
APIN
1998
98views more  APIN 1998»
13 years 7 months ago
The Evolution of Concurrent Programs
Process algebra are formal languages used for the rigorous specification and analysis of concurrent systems. By using a process algebra as the target language of a genetic program...
Brian J. Ross
EH
2004
IEEE
107views Hardware» more  EH 2004»
13 years 11 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