The traditional setting of multiagent reinforcement learning (MARL) is the mode in which there is set of agents and external environment. And the reward is given to each agent - individually or collectively - by the external environment.
My question is - is there MARL model in which the reward is given by one agent to the other agent, meaning that one agent is incurring costs and other agent - revenue (or maybe even a profit?
Effectively that means distributed supervision: only some agents face the environment with real reward/supervision and then this supervision is more or less effectively propgated to other agents that learn/do their own specialized tasks that are part of collective task ececuted/solved distributively in MARL.