System and method for multi-type mean field reinforcement machine learning

Abstract

A system for a machine reinforcement learning architecture for an environment with a plurality of agents includes: at least one memory and at least one processor configured to provide a multi-agent reinforcement learning architecture, the multi-agent reinforcement learning model based on a mean field Q function including multiple types of agents, wherein each type of agent has a corresponding mean field.