MA-BC: Provably Efficient Multi-Objective Imitation from Heterogeneous Experts

A new paper proposes MA-BC, a method for provably efficient multi-objective imitation learning from multiple experts with differing goals, balancing the information lost by naive pooling against the waste of training each expert separately.

2026-10-08 ~ 2026-10-08 · 2 related posts