Emulating the Consistency of Human Behavior with an Autonomous Robot in a Market Scenario

Mobile robots moving in a crowd need to conform to the same social standards as the human participants. Imitating human behavior is a natural choice in these situations however, not every human behaves in the same way. On the other hand, it is known that humans tend to behave in a consistent way, with their behavior predictable by their social status. In this paper we consider a marketplace where humans perform purposeful movement. With many people moving on intersecting trajectories, the participants occasionally encounter micro-conflicts, where they need to balance their desire to move towards their destination (their mission) with the requirements of the social norms of not bumping into strangers or violating their personal space. We model micro-conflicts by a series of two-player games. We show that if all humans are using consistent strategies which are aware of their own social status and can infer the social status of their opponent, the overall social costs will be lower compared to scenarios where the humans perform inconsistent strategies (even if those strategies are adaptive). We argue that robots acting in social environments should also adopt consistent strategies and align themselves with the ongoing social structure.