Prioritized experience replay in path planning via multi-dimensional transition priority fusion

INTRODUCTION: Deep deterministic policy gradient (DDPG)-based path planning algorithms for intelligent robots struggle to discern the value of experience transitions during training due to their reliance on a random experience replay. This can lead to inappropriate sampling of experience transitions...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Nuo, Wang, Peng, Zhang, Guangyuan, Ni, Cui, Nematov, Erkin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684733/
https://www.ncbi.nlm.nih.gov/pubmed/38034838
http://dx.doi.org/10.3389/fnbot.2023.1281166

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684733/
https://www.ncbi.nlm.nih.gov/pubmed/38034838
http://dx.doi.org/10.3389/fnbot.2023.1281166

Ejemplares similares