AI RESEARCH
Generalizable Multi-Task Learning for Wireless Networks Using Prompt Decision Transformers
arXiv CS.AI
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ArXi:2606.04328v1 Announce Type: cross 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. AI-driven approaches can learn complex nonlinear relationships, generalize across diverse network conditions and enable real-time, scalable and autonomous decision-making.