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GECCO
2008
Springer
157views Optimization» more  GECCO 2008»
13 years 9 months ago
Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata
Self-adaptation is used a lot in Evolutionary Strategies and with great success, yet for some reason it is not the mutation adaptation of choice for Genetic Algorithms. This poste...
Ron Breukelaar, Thomas Bäck
GECCO
2004
Springer
124views Optimization» more  GECCO 2004»
14 years 2 months ago
A Statistical Model of GA Dynamics for the OneMax Problem
A model of the dynamics of solving the counting-ones (OneMax) problem using a simple genetic algorithm (GA) is developed. It uses statistics of the early generations of GA runs to ...
Bulent Buyukbozkirli, Erik D. Goodman
GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
14 years 8 days ago
Comparing evolutionary algorithms on the problem of network inference
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
14 years 2 months ago
Adaptive genetic programming for option pricing
Genetic Programming (GP) is an automated computational programming methodology, inspired by the workings of natural evolution techniques. It has been applied to solve complex prob...
Zheng Yin, Anthony Brabazon, Conall O'Sullivan
GECCO
2003
Springer
119views Optimization» more  GECCO 2003»
14 years 1 months ago
Schema Analysis of Average Fitness in Multiplicative Landscape
By applying the schema theorem, we study the effects of crossover in Genetic Algorithms with the multiplicative fitness function. On this landscape, the analytical expression of ...
Hiroshi Furutani