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Found 3 papers, 2 papers with code
MAGNNETO: A Graph Neural Network-based Multi-Agent system for Traffic Engineering
In this paper, we present MAGNNETO, a distributed ML-based framework that leverages Multi-Agent Reinforcement Learning and Graph Neural Networks for distributed TE optimization.
Is Machine Learning Ready for Traffic Engineering Optimization?
In our evaluation, we compare our MARL+GNN system with DEFO, a network optimizer based on Constraint Programming that represents the state of the art in TE.
BIG-bench Machine Learning
Multi-agent Reinforcement Learning
+1
The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks
During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments.
