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- Q2060528 subject Q7019758.
- Q2060528 abstract "Neuroevolution, or neuro-evolution, is a form of machine learning that uses evolutionary algorithms to train artificial neural networks. It is most commonly applied in artificial life, computer games, and evolutionary robotics. A main benefit is that neuroevolution can be applied more widely than supervised learning algorithms, which require a syllabus of correct input-output pairs. In contrast, neuroevolution requires only a measure of a network's performance at a task. For example, the outcome of a game (i.e. whether one player won or lost) can be easily measured without providing labeled examples of desired strategies.".
- Q2060528 wikiPageExternalLink ANNEvolve.sourceforge.net.
- Q2060528 wikiPageExternalLink evolution-101-neuroevolution.
- Q2060528 wikiPageExternalLink nerd.x-bot.org.
- Q2060528 wikiPageExternalLink keyword?neuroevolution.
- Q2060528 wikiPageExternalLink sharpneat.sourceforge.net.
- Q2060528 wikiPageExternalLink evolutionary_learning.
- Q2060528 wikiPageExternalLink CorticalComputer.
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- Q2060528 wikiPageWikiLink Q863783.
- Q2060528 type Thing.
- Q2060528 comment "Neuroevolution, or neuro-evolution, is a form of machine learning that uses evolutionary algorithms to train artificial neural networks. It is most commonly applied in artificial life, computer games, and evolutionary robotics. A main benefit is that neuroevolution can be applied more widely than supervised learning algorithms, which require a syllabus of correct input-output pairs. In contrast, neuroevolution requires only a measure of a network's performance at a task.".
- Q2060528 label "Neuroevolution".
- Q2060528 differentFrom Q1165650.
- Q2060528 differentFrom Q1345738.
- Q2060528 differentFrom Q5418652.