Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions

ArXi:2410.07409v2 Announce Type: replace-cross From autonomous driving to package delivery, ensuring safe yet efficient multi-agent interaction is challenging as the interaction dynamics are influenced by hard-to-model factors such as social norms and contextual cues. Understanding these influences can aid in the design and evaluation of socially-aware autonomous agents whose behaviors are aligned with human values.