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Titlebook: Genetic Programming; 13th European Confer Anna Isabel Esparcia-Alcázar,Anikó Ekárt,A. ?ima U Conference proceedings 2010 Springer-Verlag Be

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41#
發(fā)表于 2025-3-28 16:37:18 | 只看該作者
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發(fā)表于 2025-3-28 19:56:11 | 只看該作者
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發(fā)表于 2025-3-29 02:25:37 | 只看該作者
https://doi.org/10.1007/978-3-662-29208-2ging may represent with good resolution GP’s behaviour in the early stages of a run, it blurs later components of the dynamics. We propose two techniques to improve the situation: solution-locked averaging and solution-time binning. Results indicate that there are significant benefits in adopting these techniques.
44#
發(fā)表于 2025-3-29 06:14:44 | 只看該作者
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發(fā)表于 2025-3-29 10:00:50 | 只看該作者
Evolving Genes to Balance a PoleThe network is a modified version of an Artificial Regulatory Network proposed a few years ago, and the task could be solved only by finding a proper way of connecting inputs and outputs to the network. We show that the representation is able to generalize well over the problem domain, and discuss the performance of different models of this kind.
46#
發(fā)表于 2025-3-29 14:44:00 | 只看該作者
Solution-Locked Averages and Solution-Time Binning in Genetic Programmingging may represent with good resolution GP’s behaviour in the early stages of a run, it blurs later components of the dynamics. We propose two techniques to improve the situation: solution-locked averaging and solution-time binning. Results indicate that there are significant benefits in adopting these techniques.
47#
發(fā)表于 2025-3-29 17:44:08 | 只看該作者
978-3-642-12147-0Springer-Verlag Berlin Heidelberg 2010
48#
發(fā)表于 2025-3-29 22:09:05 | 只看該作者
49#
發(fā)表于 2025-3-30 01:44:10 | 只看該作者
50#
發(fā)表于 2025-3-30 06:05:49 | 只看該作者
Phenotypic Diversity in Initial Genetic Programming Populations method for measuring phenotypic diversity in terms of the run-time behaviour of programs. We describe how this is applicable to a range of problem domains and show how the promotion of such diversity in initial genetic programming populations can have a substantial impact on solution-finding performance.
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