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GECCO
2003
Springer
120views Optimization» more  GECCO 2003»
15 years 9 months ago
New Usage of SOM for Genetic Algorithms
Abstract. Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM h...
Jung Hwan Kim, Byung Ro Moon
GECCO
1999
Springer
158views Optimization» more  GECCO 1999»
15 years 8 months ago
Coevolutionary Genetic Algorithms for Solving Dynamic Constraint Satisfaction Problems
In this paper, we discuss the adaptability of Coevolutionary Genetic Algorithms on dynamic environments. Our CGA consists of two populations: solution-level one and schema-level o...
Hisashi Handa, Osamu Katai, Tadataka Konishi, Mits...
GECCO
2006
Springer
202views Optimization» more  GECCO 2006»
15 years 8 months ago
Evolving hash functions by means of genetic programming
The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fa...
César Estébanez, Julio César ...
GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
15 years 8 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
15 years 5 months ago
Experiments with indexed FOR-loops in genetic programming
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...
Gayan Wijesinghe, Victor Ciesielski