Beyond Global Replanning: Hierarchical Recovery for Cross-Device Agent Systems
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Computer Science > Computation and Language
Title:Beyond Global Replanning: Hierarchical Recovery for Cross-Device Agent Systems
Abstract:Real-world computer-use tasks often span multiple applications and devices, requiring agents to coordinate heterogeneous environments under dynamic runtime failures. Existing multi-device agent systems support task decomposition and cross-device assignment, but recovery remains largely coarse-grained: when execution fails, they typically retry the same strategy, reassign the subtask, or revise the global plan, without systematically modeling the device-local strategy space. This limits their ability to distinguish failures that can be repaired within the current device from those that require cross-device replanning. We propose \textbf{H-RePlan}, a hierarchical replanning framework for multi-device agents with unified API--CLI--GUI execution. H-RePlan equips each device with interchangeable execution strategies and separates device-local strategy recovery from orchestrator-level global replanning through a compact cross-layer failure abstraction. To evaluate this capability, we introduce \textbf{HeraBench}, a fault-injected benchmark that constructs cross-device workflows over Linux and Android devices and injects strategy- and device-level failures. Experiments show that H-RePlan substantially outperforms single-strategy and coarse-grained multi-device baselines, achieving higher completion, instruction adherence, and perfect-pass rates while reducing the token cost required for reliable end-to-end success. These results demonstrate that scope-aware hierarchical recovery is essential for robust multi-device agent execution.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2606.20487 [cs.CL] |
| (or arXiv:2606.20487v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.20487
arXiv-issued DOI via DataCite (pending registration)
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