The setting considered here is coordinating with unknown human partners in zero-shot. The agent does not get to play with that particular human players for mult

The setting considered here is coordinating with unknown human partners in zero-shot. The agent does not get to play with that particular human players for multiple runs. It is a motivating example to show what a grounded policy is and why it may be desirable in real world situations. In complex environments RL method may learn arbitrary complex strategies/conventions when trained in simulations, making it hard to deploy in real time for human-AI collaborations. Even when multiple runs of interactions are available, it is challenging to fine-tune a policy on the fly given the very limited amount of data.