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» Data Mining for Genetics: A Genetic Algorithm Approach
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GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
15 years 10 months ago
Soft memory for stock market analysis using linear and developmental genetic programming
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...
Garnett Carl Wilson, Wolfgang Banzhaf
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 5 months ago
Memory with memory: soft assignment in genetic programming
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
Nicholas Freitag McPhee, Riccardo Poli
131
Voted
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 10 months ago
Coevolution of intelligent agents using cartesian genetic programming
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....
155
Voted
GECCO
2008
Springer
154views Optimization» more  GECCO 2008»
15 years 5 months ago
Automated shape composition based on cell biology and distributed genetic programming
Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell i...
Linge Bai, Manolya Eyiyurekli, David E. Breen
EVOW
2001
Springer
15 years 8 months ago
An Evolutionary Annealing Approach to Graph Coloring
This paper presents a new heuristic algorithm for the graph coloring problem based on a combination of genetic algorithms and simulated annealing. Our algorithm exploits a novel cr...
Dimitris Fotakis, Spiridon D. Likothanassis, Stama...