Cargando…
Maximizing adaptive power in neuroevolution
In this paper we compare systematically the most promising neuroevolutionary methods and two new original methods on the double-pole balancing problem with respect to: the ability to discover solutions that are robust to variations of the environment, the speed with which such solutions are found, a...
Autores principales: | Pagliuca, Paolo, Milano, Nicola, Nolfi, Stefano |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051599/ https://www.ncbi.nlm.nih.gov/pubmed/30020942 http://dx.doi.org/10.1371/journal.pone.0198788 |
Ejemplares similares
-
Robust optimization through neuroevolution
por: Pagliuca, Paolo, et al.
Publicado: (2019) -
Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization
por: Pagliuca, Paolo, et al.
Publicado: (2020) -
Hands-On Neuroevolution with Python
por: Omelianenko, Iaroslav
Publicado: (2019) -
Correspondence between neuroevolution and gradient descent
por: Whitelam, Stephen, et al.
Publicado: (2021) -
Towards the Neuroevolution of Low-level artificial general intelligence
por: Pontes-Filho, Sidney, et al.
Publicado: (2022)