Temporally Consistent Graph Q-Networks for Intelligent Network Control

arXiv:2606.13848 · cs.NI, cs.LG · Submitted 2026-06-11 · Read on arXiv

cs.NI, cs.LG

Submitted: 2026-06-11

Updated: 2026-06-11

Comments: 7 pages, 5 figures. Accepted to the 6G AI-RAN Workshop at IEEE INFOCOM 2026. The final published version will be available via IEEE Xplore

Journal ref: IEEE INFOCOM 2026 - IEEE Conference on Computer Communications, 2026

DOI: 10.1109/INFOCOM59046.2026.11571413

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 12× in this paper · explained in 4 episodes
• Reward Function — 9× in this paper · explained in 2 episodes
• Adaptation — 8× in this paper · explained in 1 episode
• Embeddings — 7× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Representation Learning — 5× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Temporal consistency — 4× in this paper · explained in 2 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Attention Mechanism — 3× in this paper · explained in 3 episodes
• Cooperation — 3× in this paper · explained in 2 episodes
• GNNs — 3× in this paper · explained in 2 episodes
• Temporally Consistent Graph Q-Networks — 3× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Energy Efficiency — 2× in this paper · explained in 3 episodes
• Multi-Agent Reinforcement Learning (MARL) — 2× in this paper · explained in 4 episodes
• Sample Efficiency — 2× in this paper · explained in 4 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Dec-POMDP — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Transformer — 1× in this paper · explained in 2 episodes

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