Multiagent systems deployed in the real world need to cooperate with other agents (including humans) nearly as effectively as these agents cooperate with one another. To design such AI, and provide guarantees of its effectiveness, we need to clearly specify what types of agents our AI must be able to cooperate with. In this work we propose a generic model of socially intelligent agents, which are individually rational learners that are also able to cooperate with one another (in the sense that their joint behavior is Pareto efficient). We define rationality in terms of the regret incurred by each agent over its lifetime, and show how we can construct socially intelligent agents for different forms of regret. We then discuss the implications of this model for the development of "robust" MAS that can cooperate with a wide variety of socially intelligent agents.

翻译：现实世界中部署的多智能体系统需要与其他智能体（包括人类）进行近乎高效的合作，其合作水平需达到这些智能体彼此之间的协作程度。为设计此类人工智能并确保其有效性，我们必须明确界定AI需要能够合作的智能体类型。本文提出了一种通用社会智能体模型，这些智能体既是独立理性学习者，又能相互协作（其联合行为符合帕累托最优）。我们以每个智能体在其生命周期内产生的遗憾值来定义理性，并展示了如何针对不同形式的遗憾值构建社会智能体。最后，我们讨论了该模型对开发能够与广泛社会智能体协作的“鲁棒”多智能体系统的启示。