Provably Stable Multi-Agent Routing with Bounded-Delay Adversaries in the Decision Loop
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866910900945944576 |
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| author | Francos, Roee M. Garces, Daniel Gil, Stephanie |
| author_facet | Francos, Roee M. Garces, Daniel Gil, Stephanie |
| contents | In this work, we are interested in studying multi-agent routing settings, where adversarial agents are part of the assignment and decision loop, degrading the performance of the fleet by incurring bounded delays while servicing pickup-and-delivery requests. Specifically, we are interested in characterizing conditions on the fleet size and the proportion of adversarial agents for which a routing policy remains stable, where stability for a routing policy is achieved if the number of outstanding requests is uniformly bounded over time. To obtain this characterization, we first establish a threshold on the proportion of adversarial agents above which previously stable routing policies for fully cooperative fleets are provably unstable. We then derive a sufficient condition on the fleet size to recover stability given a maximum proportion of adversarial agents. We empirically validate our theoretical results on a case study on autonomous taxi routing, where we consider transportation requests from real San Francisco taxicab data. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2504_00863 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Provably Stable Multi-Agent Routing with Bounded-Delay Adversaries in the Decision Loop Francos, Roee M. Garces, Daniel Gil, Stephanie Multiagent Systems Robotics In this work, we are interested in studying multi-agent routing settings, where adversarial agents are part of the assignment and decision loop, degrading the performance of the fleet by incurring bounded delays while servicing pickup-and-delivery requests. Specifically, we are interested in characterizing conditions on the fleet size and the proportion of adversarial agents for which a routing policy remains stable, where stability for a routing policy is achieved if the number of outstanding requests is uniformly bounded over time. To obtain this characterization, we first establish a threshold on the proportion of adversarial agents above which previously stable routing policies for fully cooperative fleets are provably unstable. We then derive a sufficient condition on the fleet size to recover stability given a maximum proportion of adversarial agents. We empirically validate our theoretical results on a case study on autonomous taxi routing, where we consider transportation requests from real San Francisco taxicab data. |
| title | Provably Stable Multi-Agent Routing with Bounded-Delay Adversaries in the Decision Loop |
| topic | Multiagent Systems Robotics |
| url | https://arxiv.org/abs/2504.00863 |