DynAMO:Dynamic Asset Management Orchestration via Topological Multi-Agent Scheduling 文章

ArXiv CS.AI2026-06-19NEWSen作者: Kanishk Kushwaha, Vikrant Vinod Bansode, Harsh Vardhan, Dhaval C. Patel

详细信息

来源站点
ArXiv CS.AI
作者
Kanishk Kushwaha, Vikrant Vinod Bansode, Harsh Vardhan, Dhaval C. Patel
文章类型
NEWS
语言
en
发布日期
2026-06-19

摘要

arXiv:2606.19382v1 Announce Type: cross Abstract: While LLM-powered agents offer end-to-end automation for industrial asset lifecycles, real-world Industry 4.0 deployment is hindered by latency, concurrency instability, and safety risks. We present DynAMO (Dynamic Asset Management Orchestration), a deployment-ready engine using a Plan-then-Execute architecture to generate verifiable workflow graphs. DynAMO supports both SequentialWorkflow (topological execution) and ParallelWorkflow (dependency-aware concurrency). By dynamically identifying independent tasks, DynAMO preserves structural correctness and safety while significantly improving efficiency through controlled reasoning overlap. Across six controlled experiments on the AssetOpsBench industrial benchmark, DynAMO demonstrates substantial performance and robustness gains. Parallel execution reduces end-to-end latency by a median of 1.6x over sequential orchestration, rising to 1.8x on highly parallelizable workflows.

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