Speeding Task Allocation Search for Reconfigurations in Adaptive Distributed Embedded Systems Using Deep Reinforcement Learning

A Critical Adaptive Distributed Embedded System (CADES) is a group of interconnected nodes that must carry out a set of tasks to achieve a common goal, while fulfilling several requirements associated with their critical (e.g., hard real-time requirements) and adaptive nature. In these systems, a ke...

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Detalles Bibliográficos
Autores principales: Rotaeche, Ramón, Ballesteros, Alberto, Proenza, Julián
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823603/
https://www.ncbi.nlm.nih.gov/pubmed/36617145
http://dx.doi.org/10.3390/s23010548

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823603/
https://www.ncbi.nlm.nih.gov/pubmed/36617145
http://dx.doi.org/10.3390/s23010548

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