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» Adapting binary fitness functions in Genetic Algorithms
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GECCO
2007
Springer
151views Optimization» more  GECCO 2007»
15 years 3 months ago
A building-block royal road where crossover is provably essential
One of the most controversial yet enduring hypotheses about what genetic algorithms (GAs) are good for concerns the idea that GAs process building-blocks. More specifically, it ha...
Richard A. Watson, Thomas Jansen
ICGA
1993
145views Optimization» more  ICGA 1993»
14 years 11 months ago
Genetic Programming of Minimal Neural Nets Using Occam's Razor
A genetic programming method is investigated for optimizing both the architecture and the connection weights of multilayer feedforward neural networks. The genotype of each networ...
Byoung-Tak Zhang, Heinz Mühlenbein
GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
14 years 1 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto
JFP
2006
113views more  JFP 2006»
14 years 9 months ago
Efficient manipulation of binary data using pattern matching
Pattern matching is an important operation in functional programs. So far, pattern matching has been investigated in the context of structured terms. This article presents an appr...
Per Gustafsson, Konstantinos F. Sagonas
66
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CEC
2007
IEEE
15 years 1 months ago
A versatile quantum-inspired evolutionary algorithm
Abstract-- This study points out some weaknesses of existing Quantum-Inspired Evolutionary Algorithms (QEA) and explains in particular how hitchhiking phenomenons can slow down the...
Michael Defoin-Platel, Stefan Schliebs, Nikola Kas...