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Permutation Robustness Is Not Enough: Action Collapse in Multi-Agent Transformer Policies
Transformer policies are attractive for multi-agent robot learning because self-attention can model interactions among agents. However, multi-agent teams are unordered, while transformers typically process agents as ordered token sequences. We study how this mismatch affects cooperative navigation p
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