The work develops an iterative safe planner that adjusts conformal prediction bounds across policy updates via sensitivity analysis to maintain distribution-free safety guarantees despite interaction-induced distribution shifts.
Probabilistically correct language-based multi-robot planning using conformal prediction
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Safe Planning in Interactive Environments via Iterative Policy Updates and Adversarially Robust Conformal Prediction
The work develops an iterative safe planner that adjusts conformal prediction bounds across policy updates via sensitivity analysis to maintain distribution-free safety guarantees despite interaction-induced distribution shifts.