A two-tier agent framework with compositional reinforcement learning and predictive decision-making reduces handover failures, improves KPIs, and accelerates training in simulated self-organizing networks.
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Compositional Learning for Modular Multi-Agent Self-Organizing Networks
A two-tier agent framework with compositional reinforcement learning and predictive decision-making reduces handover failures, improves KPIs, and accelerates training in simulated self-organizing networks.