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Autonomous learning of features for control: Experiments with embodied and situated agents
The efficacy of evolutionary or reinforcement learning algorithms for continuous control optimization can be enhanced by including an additional neural network dedicated to features extraction trained through self-supervision. In this paper we introduce a method that permits to continue the training...
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| Publicat a: | PLoS One |
|---|---|
| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Public Library of Science
2021
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8049238/ https://ncbi.nlm.nih.gov/pubmed/33857220 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0250040 |
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