Using Feasible Action-Space Reduction by Groups to fill Causal Responsibility Gaps in Spatial Interactions

TL;DR

This paper introduces a novel group-based causal responsibility metric for spatial interactions, addressing limitations of individual-focused metrics in multi-agent scenarios involving autonomous systems.

Contribution

It formulates a group causal responsibility metric, defines assertive influence types, and proposes a tiering algorithm to identify responsible agents in spatial interactions.

Findings

Group responsibility metrics fill gaps in causal attribution.

The tiering algorithm systematically identifies assertive agents.

Simulations show group effects vary with interaction dynamics.

Abstract

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.