MA-BC partitions divergent expert data and pools non-conflicting pairs to achieve faster convergence to Pareto-optimal policies in MOMDPs, with a matching minimax lower bound.
24 Then, we have that max M∈{M 1
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Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation
MA-BC partitions divergent expert data and pools non-conflicting pairs to achieve faster convergence to Pareto-optimal policies in MOMDPs, with a matching minimax lower bound.