From Proposal to Execution: Modeling Interaction Semantics in Shared Autonomy
In many human-AI systems, candidate actions are not executed directly but are first evaluated by another decision-making entity under a potentially different objective or decision model. Standard decision-theoretic frameworks do not require this interaction to be represented explicitly, as they define transition dynamics directly over state-action pairs, allowing evaluation to be absorbed within the transition model. We introduce a semantics-aware decision framework in which a candidate action is proposed, evaluated under an interaction context, and then resolved into an executed outcome. We formalize this through a joint action language and an interpretation function that maps each joint...
| Authors | Shashank Shekhar, Laurent Jeanpierre, Abdel-Illah Mouaddib |
|---|---|
| Primary category | cs.AI |
| Published | 18 October 2026 |
| Last updated at source | 20 October 2026 |
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