SPIN: Decentralized Swarm Control via Tensorized Policy Coordination
Decentralized multi-agent swarm coordination remains fundamentally challenged by the combinatorial scaling of joint action spaces and high-overhead training or optimization loops when managing localized group behaviors. To address this problem from a different perspective, this paper introduces the Swarm Policy Interference Network (SPIN) framework, which models multi-agent communication topologies as compressed tensor networks. By factorizing the joint policy tensors of local multi-agent cliques into Open Boundary Condition Matrix Product State (MPS) chains, SPIN replaces explicit exponential joint-action enumeration with clique-level contractions that scale linearly in clique length for...
| Authors | Zhaowen Fan, Yunxiang Han |
|---|---|
| Primary category | cs.LG |
| Published | 25 May 2026 |
| Last updated at source | 20 July 2026 |
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