Our paper Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems was accepted to NeurIPS! It shows how influence-based abstraction can be used to parallelize and thus speed up multiagent reinforcement learning, while stabilizing the learning at the same time.