Network Parameter Control in Cellular Networks through Graph-Based Multi-Agent Constrained Reinforcement Learning
Albin Larsson Forsberg,
Alexandros Nikou,
Aneta Vulgarakis Feljan
et al.
Abstract:Cellular networks are growing in complexity at increasing speed and the geographical locations in which they are deployed in are getting denser. Traditional control methods fall short in providing a scalable and dynamic way of adapting the network to new conditions. Distributed multiagent reinforcement learning successfully addresses scalability problems seen in centralized approaches. The question of achieving learning with constraint satisfaction in distributed systems is still left unanswered in the state-o… Show more
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