AINeutralarXiv – CS AI · 9h ago6/10
🧠
A Unified Framework for Locality in Scalable MARL
Researchers present a unified mathematical framework for certifying locality in scalable multi-agent reinforcement learning (MARL) systems by decomposing the state-transition matrix into environment and policy sensitivity components. The approach uses spectral radius analysis to weaken prior Dobrushin bounds and applies temperature-scaled softmax policies to control locality, enabling exponentially decaying truncation bias in networked agent systems.