Heralding the advent of autonomous vehicles and mobile robots that interact with humans, responsibility in spatial interaction is burgeoning as a research topic. Even though metrics of responsibility tailored to spatial interactions have been proposed, they are mostly focused on the responsibility of individual agents. Metrics of causal responsibility focusing on individuals fail in cases of causal overdeterminism -- when many actors simultaneously cause an outcome. To fill the gaps in causal responsibility left by individual-focused metrics, we formulate a metric for the causal responsibility of groups. To identify assertive agents that are causally responsible for the trajectory of an affected agent, we further formalise the types of assertive influences and propose a tiering algorithm for systematically identifying assertive agents. Finally, we use scenario-based simulations to illustrate the benefits of considering groups and how the emergence of group effects vary with interaction dynamics and the proximity of agents.

翻译：随着自动驾驶车辆和移动机器人等与人类交互的自主系统的兴起，空间交互中的责任归属正成为一个新兴研究课题。尽管已有针对空间交互场景定制的责任度量方法，但这些方法主要聚焦于个体智能体的责任评估。在因果过度决定情形下——即多个行为主体同时导致某一结果时，专注于个体的因果责任度量方法将失效。为填补个体导向度量方法遗留的因果责任空白，本文构建了一种面向群体的因果责任度量框架。为识别对受影响智能体轨迹具有因果责任的主动型智能体，我们进一步形式化了主动影响的类型，并提出用于系统识别主动型智能体的分层算法。最后，通过基于场景的仿真实验，我们展示了群体考量方法的优势，并揭示了群体效应如何随交互动力学特性与智能体空间邻近度而演变。