Active learning strategies for preference-based MPC objective learning achieve better closed-loop alignment with human preferences using fewer queries than random sampling in numerical tests.
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Active Learning MPC Objective Functions from Preferences
Active learning strategies for preference-based MPC objective learning achieve better closed-loop alignment with human preferences using fewer queries than random sampling in numerical tests.