It'd be interesting if the agents developed their own language during the reinforcement learning stage that is unintelligible to humans but allows them to quickly navigate the negotiation. They use the model trained in a supervised way during the reinforcement learning stage to avoid this, but I'm curious to see what the agent learns when paired against another reinforcement learning agent.

Edit: Indeed, the paper says that not using the fixed agent trained on human negotiation leads to unintelligible language from the agents.