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GECCO
2000
Springer
120views Optimization» more  GECCO 2000»
15 years 1 months ago
A Note on Learning and Evolution in Neural Networks
Interactions between evolution and lifetime learning are of great interest to studies of adaptive behaviour both in the natural world and the field of evolutionary computation. Th...
Brian Carse, Johan Oreland
GECCO
2000
Springer
121views Optimization» more  GECCO 2000»
15 years 1 months ago
Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models
In this paper we describe a method for improving genetic-algorithm-based optimization using informed genetic operators. The idea is to make the genetic operators such as mutation ...
Khaled Rasheed, Haym Hirsh
GECCO
2000
Springer
15 years 1 months ago
Modeling GA Performance for Control Parameter Optimization
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...
Vincent A. Cicirello, Stephen F. Smith
GECCO
2000
Springer
225views Optimization» more  GECCO 2000»
15 years 1 months ago
Solving Large Binary Quadratic Programming Problems by Effective Genetic Local Search Algorithm
A genetic local search (GLS) algorithm, which is a combination technique of genetic algorithm and local search, for the unconstrained binary quadratic programming problem (BQP) is...
Kengo Katayama, Masafumi Tani, Hiroyuki Narihisa
GECCO
2000
Springer
158views Optimization» more  GECCO 2000»
15 years 1 months ago
Grammar based function definition in Grammatical Evolution
We describe the use of grammars as an approach to automatic function definition in Grammatical Evolution. The automatic generation of functions allows the evolution of both the fu...
Michael O'Neill, Conor Ryan