AI RESEARCH
ARMATA: Auto-Regressive Multi-Agent Task Assignment
arXiv CS.AI
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ArXi:2605.04225v1 Announce Type: cross Coordinating multi-agent systems over spatially distributed areas requires solving a complex hierarchical problem: first distributing areas among agents (allocation) and subsequently determining the optimal visitation order (routing). Existing methods typically decouple these stages ignoring inter-stage dependencies or rely on decentralized heuristics that lack global context. In this work, we propose a centralized, fully end-to-end auto-regressive framework that jointly generates allocation decisions and routing sequences.