3 papers
cs.LG2026
From Intents to Actions: Agentic AI in Autonomous Networks
Burak Demirel, Pablo Soldati, Yu Wang
Telecommunication networks are increasingly expected to operate autonomously while supporting heterogeneous services with diverse and often conflicting intents -- that is, performa…
cs.LG2026
Practical Policy Distillation for Reinforcement Learning in Radio Access Networks
Sara Khosravi, Burak Demirel, Linghui Zhou +2
Adopting artificial intelligence (AI) in radio access networks (RANs) presents several challenges, including limited availability of link-level measurements (e.g., CQI reports), st…
cs.LG2026
Generalization in Reinforcement Learning for Radio Access Networks
Burak Demirel, Yu Wang, Cristian Tatino +1
Modern RAN operate in highly dynamic and heterogeneous environments, where hand-tuned, rule-based RRM algorithms often underperform. While RL can surpass such heuristics in constra…