Improving the Traffic Engineering of SDN networks by using Local Multi-Agent Deep Reinforcement Learning

Literals

• vivo:identifier
  • 2024-2930
• dcterms:contributor
• dcterms:creator
  • Gomez-Delahiz J.
• bibo:doi
  • 10.1109/noms59830.2024.10575465
• ou:eid
  • 2-s2.0-85198323084
• fabio:hasPublicationYear
  • 2024
• bibo:isbn
  • 9798350327939
• dcterms:publisher
  • Proceedings of IEEE/IFIP Network Operations and Management Symposium 2024, NOMS 2024
• ou:tipoPublicacion
  • Conference Paper
• dcterms:title
  • Improving the Traffic Engineering of SDN networks by using Local Multi-Agent Deep Reinforcement Learning
• vcard:url
  • https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85198323084&origin=inward
• ou:urlScopus
  • https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85198323084&origin=inward

Typed Literals

• ou:vecesCitado
  • 2 (xsd:integer)

Inverse Relations

• Has related: ou:tienePublicacion
  • JAIME GALÁN JIMÉNEZ