Corrigible Assistance in One Round: Pragmatic-Pedagogic Best Response
Assistance games formalize human-robot collaboration under asymmetric information: the human knows the goal, while the robot must infer it from observation and interaction in order to assist effectively. In general, computing optimal assistance game strategies online is intractable, since exact solutions require planning in a POMDP. We identify a class of assistance games in which pragmatic-pedagogic reasoning resolves goal uncertainty in a single time step, rendering the full-horizon game exactly solvable by a tractable best-response procedure. Within this class, we show that mainstream inverse optimal control exhibits an inference ceiling that hinders alignment, while pragmatic-pedagogi...
| Authors | Elle Lazarski, Jaime Fernández Fisac |
|---|---|
| Primary category | cs.RO |
| Published | 29 July 2026 |
| Last updated at source | 29 July 2026 |
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