arXiv Machine Learning By Ali Al Housseini, Cristina Rottondi, Sebastian Troia, Omran Ayoub

Exploiting the Alternatives: Coordinated Learning via Hierarchical RL for Dynamic VNEAP

Read the original on arXiv Machine Learning →

arXiv:2512. 05207v3 Announce Type: replace-cross Abstract: Virtual Network Embedding (VNE) is a key enabler of network slicing, yet most formulations assume that each Virtual Network Request (VNR) has a fixed topology.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jul 13

Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning

arXiv:2504. 18902v3 Announce Type: replace-cross Abstract: In the forthcoming era of 6G networks, characterized by unprecedented data rates, ultra-low latency, and ubiquitous connectivity, effective management of Virtualized Network Functions (VNFs) is essential.

By Cyril Shih-Huan Hsu, Anestis Dalgkitsis, Paola Grosso, Chrysa Papagianni
arXiv AI
Jun 4

Generalizable Multi-Task Learning for Wireless Networks Using Prompt Decision Transformers

arXiv:2606. 04328v1 Announce Type: cross Abstract: Future wireless networks demand rapid adaptation to highly heterogeneous environments and dynamic task configurations, necessitating a shift from conventional rule-based and optimization-driven radio resource management (RRM) toward artificial intelligence (AI)-driven RRM.

By Fatih Temiz, Shavbo Salehi, Melike Erol-Kantarci