ARMATA: Auto-Regressive Multi-Agent Task Assignment
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. The core contribution of our approach is a multi-stage decoding mechanism that unifies high-level allocation and low-level routing in a single autoregressive pass whil...
| Authors | Yazan Youssef, Aboelmagd Noureldin, Sidney Givigi |
|---|---|
| Primary category | cs.MA |
| Published | 5 May 2026 |
| Last updated at source | 5 May 2026 |
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