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Parallel bi-state deep reinforcement learning approach for SFC placements and deployments.

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Title: Parallel bi-state deep reinforcement learning approach for SFC placements and deployments.
Authors: Khemili, Wided1,2, wided.khemili@edu.univ-paris13.fr, Saidi, Mohand Yazid2, saidi@univ-paris13.fr, Hajlaoui, Jalel Eddine3, jaleleddine.hajlaoui@epfedu.fr, Omri, Mohamed Nazih3,4, mohamednazih.omri@eniso.u-sousse.tn, Chen, Ken2, ken.chen@univ-paris13.fr
Source: Neural Computing & Applications; Oct2025, Vol. 37 Issue 30, p24541-24560, 20p
Database: Applied Science & Technology Source
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Header DbId: aci
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  Data: Parallel bi-state deep reinforcement learning approach for SFC placements and deployments.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=188547146
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s00521-024-10486-7
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      – Code: eng
        Text: English
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        StartPage: 24541
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      – TitleFull: Parallel bi-state deep reinforcement learning approach for SFC placements and deployments.
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            NameFull: Khemili, Wided
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              Text: Oct2025
              Type: published
              Y: 2025
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