دورية أكاديمية
Autonomous learning of features for control: Experiments with embodied and situated agents.
| العنوان: | Autonomous learning of features for control: Experiments with embodied and situated agents. |
|---|---|
| المؤلفون: | Nicola Milano, Stefano Nolfi |
| المصدر: | PLoS ONE, Vol 16, Iss 4, p e0250040 (2021) |
| بيانات النشر: | Public Library of Science (PLoS), 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | 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 of the features extracting network during the training of the control network. We demonstrate that the parallel training of the two networks is crucial in the case of agents that operate on the basis of egocentric observations and that the extraction of features provides an advantage also in problems that do not benefit from dimensionality reduction. Finally, we compare different feature extracting methods and we show that sequence-to-sequence learning outperforms the alternative methods considered in previous studies. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1932-6203 |
| Relation: | https://doaj.org/toc/1932-6203 |
| DOI: | 10.1371/journal.pone.0250040 |
| URL الوصول: | https://doaj.org/article/c7418941452c4e82b10344cbcae3f066 |
| رقم الأكسشن: | edsdoj.7418941452c4e82b10344cbcae3f066 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19326203 |
|---|---|
| DOI: | 10.1371/journal.pone.0250040 |