KD-MARL: Efficient Knowledge Distillation for Edge-Ready Multi-Agent Systems
Researchers propose a new method for resource-aware knowledge distillation in multi-agent reinforcement learning (MARL). The approach addresses the challenges of deploying expert policies on edge devices by focusing on coordination structure and heterogeneous agent capabilities.