We propose a method, based on empirical game theory, for a robot operating as part of a team to choose its role within the team without explicitly communicating with team members, by leveraging its knowledge about the team structure. To do this, we formulate the role assignment problem as a dynamic game, and borrow tools from empirical game-theoretic analysis to analyze such games. Based on this game-theoretic formulation, we propose a distributed controller for each robot to dynamically decide on the best role to take. We demonstrate our method in simulations of a collaborative planar manipulation scenario in which each agent chooses from a set of feedback control policies at each instant. The agents can effectively collaborate without communication to manipulate the object while also avoiding collisions using our method.

翻译：我们根据实证游戏理论,提出一种方法,让作为团队一部分运作的机器人在团队中选择自己的角色,而不与团队成员明确沟通,方法是利用其对团队结构的了解。为此,我们将角色分配问题设计为动态游戏,并借用实证游戏理论分析工具来分析此类游戏。基于这种游戏理论配方,我们建议为每个机器人配置一个分布式控制器,以动态地决定最佳角色。我们在模拟协作计划操纵情景时展示了我们的方法,其中每个代理从每瞬间一组反馈控制政策中选择。代理可以有效协作,无需通信即可操纵对象,同时使用我们的方法避免碰撞。