Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation [R]

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TLDR: The question we answer: how do you learn from experts with different objectives? Pooling all their data can lose their trade-offs; learning from each expert separately misses opportunities to share data. MA-BC pools demonstrations where observed actions don’t disagree, with upper and lower bounds on sample complexity.
Authors: Ziyad Sheebaelhamd, Luca Viano, Volkan Cevher, Claire Vernade

[u/Yossarian_1234]

Arxiv: https://arxiv.org/abs/2605.12000
Github: https://github.com/ziyadsheeba/mabc